www.manning.com
Open in
urlscan Pro
35.166.24.88
Public Scan
Effective URL: https://www.manning.com/books/deep-learning-with-python?trk_msg=1N7MRLO71AFK90KC22T57LIBMS&trk_contact=G9HFC3C7369KLN78R...
Submission: On August 03 via api from US
Summary
TLS certificate: Issued by Go Daddy Secure Certificate Authority... on May 20th 2016. Valid for: 3 years.
This is the only time www.manning.com was scanned on urlscan.io!
urlscan.io Verdict: No classification
Domain & IP information
IP Address | AS Autonomous System | ||
---|---|---|---|
1 1 | 142.0.93.10 142.0.93.10 | 394396 (LISTRAK-AS1) (LISTRAK-AS1 - Listrak) | |
2 24 | 35.166.24.88 35.166.24.88 | 16509 (AMAZON-02) (AMAZON-02 - Amazon.com) | |
1 | 2a00:1450:400... 2a00:1450:4001:814::200a | 15169 (GOOGLE) (GOOGLE - Google LLC) | |
1 | 2a00:1450:400... 2a00:1450:4001:814::2008 | 15169 (GOOGLE) (GOOGLE - Google LLC) | |
28 | 184.173.95.35 184.173.95.35 | 36351 (SOFTLAYER) (SOFTLAYER - SoftLayer Technologies Inc.) | |
2 | 139.162.206.25 139.162.206.25 | 63949 (LINODE-AP...) (LINODE-AP Linode) | |
1 3 | 2a00:1450:400... 2a00:1450:4001:81d::200e | 15169 (GOOGLE) (GOOGLE - Google LLC) | |
2 | 2a03:2880:f01... 2a03:2880:f01c:8012:face:b00c:0:3 | 32934 (FACEBOOK) (FACEBOOK - Facebook) | |
1 | 2a00:1450:400... 2a00:1450:400c:c00::9a | 15169 (GOOGLE) (GOOGLE - Google LLC) | |
3 | 2a03:2880:f11... 2a03:2880:f11c:8186:face:b00c:0:50fb | 32934 (FACEBOOK) (FACEBOOK - Facebook) | |
2 | 52.84.121.220 52.84.121.220 | 16509 (AMAZON-02) (AMAZON-02 - Amazon.com) | |
4 | 2a00:1450:400... 2a00:1450:4001:81d::2003 | 15169 (GOOGLE) (GOOGLE - Google LLC) | |
2 | 52.204.71.90 52.204.71.90 | 14618 (AMAZON-AES) (AMAZON-AES - Amazon.com) | |
70 | 12 |
ASN394396 (LISTRAK-AS1 - Listrak, US)
enews.manning.com |
ASN16509 (AMAZON-02 - Amazon.com, Inc., US)
PTR: ec2-35-166-24-88.us-west-2.compute.amazonaws.com
www.manning.com | |
login.manning.com |
ASN36351 (SOFTLAYER - SoftLayer Technologies Inc., US)
PTR: 23.5f.adb8.ip4.static.sl-reverse.com
images.manning.com |
ASN63949 (LINODE-AP Linode, LLC, US)
PTR: li1369-25.members.linode.com
manning.postaffiliatepro.com |
ASN32934 (FACEBOOK - Facebook, Inc., US)
connect.facebook.net |
ASN32934 (FACEBOOK - Facebook, Inc., US)
www.facebook.com |
ASN16509 (AMAZON-02 - Amazon.com, Inc., US)
PTR: server-52-84-121-220.iad16.r.cloudfront.net
cdn.listrakbi.com |
ASN14618 (AMAZON-AES - Amazon.com, Inc., US)
PTR: ec2-52-204-71-90.compute-1.amazonaws.com
s1.listrakbi.com |
Apex Domain Subdomains |
Transfer | |
---|---|---|
53 |
manning.com
3 redirects
enews.manning.com www.manning.com images.manning.com login.manning.com |
5 MB |
4 |
gstatic.com
fonts.gstatic.com |
57 KB |
4 |
listrakbi.com
cdn.listrakbi.com s1.listrakbi.com |
48 KB |
3 |
facebook.com
www.facebook.com |
539 B |
3 |
google-analytics.com
1 redirects
www.google-analytics.com |
16 KB |
2 |
facebook.net
connect.facebook.net |
30 KB |
2 |
postaffiliatepro.com
manning.postaffiliatepro.com |
8 KB |
1 |
doubleclick.net
stats.g.doubleclick.net |
305 B |
1 |
googletagmanager.com
www.googletagmanager.com |
24 KB |
1 |
googleapis.com
fonts.googleapis.com |
902 B |
70 | 10 |
Domain | Requested by | |
---|---|---|
28 | images.manning.com |
www.manning.com
connect.facebook.net |
19 | www.manning.com |
1 redirects
www.manning.com
connect.facebook.net |
5 | login.manning.com |
1 redirects
www.manning.com
|
4 | fonts.gstatic.com |
www.manning.com
connect.facebook.net |
3 | www.facebook.com |
www.manning.com
|
3 | www.google-analytics.com |
1 redirects
www.googletagmanager.com
www.google-analytics.com |
2 | s1.listrakbi.com |
cdn.listrakbi.com
|
2 | cdn.listrakbi.com |
www.manning.com
cdn.listrakbi.com |
2 | connect.facebook.net |
www.manning.com
connect.facebook.net |
2 | manning.postaffiliatepro.com |
www.manning.com
manning.postaffiliatepro.com |
1 | stats.g.doubleclick.net |
www.manning.com
|
1 | www.googletagmanager.com |
www.manning.com
|
1 | fonts.googleapis.com |
www.manning.com
|
1 | enews.manning.com | 1 redirects |
70 | 14 |
This site contains links to these domains. Also see Links.
Domain |
---|
login.manning.com |
freecontent.manning.com |
forums.manning.com |
www.facebook.com |
twitter.com |
www.youtube.com |
livebook.manning.com |
manning-content.s3.amazonaws.com |
github.com |
Subject Issuer | Validity | Valid | |
---|---|---|---|
*.manning.com Go Daddy Secure Certificate Authority - G2 |
2016-05-20 - 2019-05-25 |
3 years | crt.sh |
This page contains 1 frames:
Primary Page:
https://www.manning.com/books/deep-learning-with-python?trk_msg=1N7MRLO71AFK90KC22T57LIBMS&trk_contact=G9HFC3C7369KLN78RN71TFVR4C&trk_sid=AJ5TFHL416GMJT7TQRL9SLD7QC&utm_source=Listrak&utm_medium=Email&utm_term=https%3a%2f%2fwww.manning.com%2fbooks%2fdeep-learning-with-python&utm_campaign=Just+12+hours+left%e2%80%94Half+off+all+pBooks+TODAY+ONLY!
Frame ID: 6812C92573AE181DD21A1C0E2FF03D43
Requests: 70 HTTP requests in this frame
Screenshot
Page URL History Show full URLs
-
http://enews.manning.com/q/hY89T9cUICXUT0X2ixaVHnTE71v-T1wfaeAZcOJa2FpdGxpbi5wb3LdlbGxAY2FwaXRhbG9uZS...
HTTP 302
https://www.manning.com/books/deep-learning-with-python?trk_msg=1N7MRLO71AFK90KC22T57LIBMS&trk_conta... Page URL
Detected technologies
Nginx (Web Servers) ExpandDetected patterns
- headers server /nginx(?:\/([\d.]+))?/i
React (JavaScript Frameworks) Expand
Detected patterns
- env /^React$/i
Facebook (Widgets) Expand
Detected patterns
- script /\/\/connect\.facebook\.net\/[^\/]*\/[a-z]*\.js/i
Google Analytics (Analytics) Expand
Detected patterns
- script /google-analytics\.com\/(?:ga|urchin|(analytics))\.js/i
- env /^gaGlobal$/i
Google Font API (Font Scripts) Expand
Detected patterns
- html /<link[^>]* href=[^>]+fonts\.(?:googleapis|google)\.com/i
Google Tag Manager (Tag Managers) Expand
Detected patterns
- env /^google_tag_manager$/i
Moment.js (JavaScript Libraries) Expand
Detected patterns
- env /^moment$/i
jQuery (JavaScript Libraries) Expand
Detected patterns
- env /^jQuery$/i
Page Statistics
274 Outgoing links
These are links going to different origins than the main page.
Title: sign out
Search URL Search Domain Scan URL
Title: free content
Search URL Search Domain Scan URL
Title: forums
Search URL Search Domain Scan URL
Title: Manning on Facebook
Search URL Search Domain Scan URL
Title: Manning on Twitter
Search URL Search Domain Scan URL
Title: Manning on YouTube
Search URL Search Domain Scan URL
Title: livebook
Search URL Search Domain Scan URL
Title: Deep Learning with Python François Chollet Look inside
Search URL Search Domain Scan URL
Title: Chapter 1
Search URL Search Domain Scan URL
Title: Chapter 2
Search URL Search Domain Scan URL
Title: Chapter 3
Search URL Search Domain Scan URL
Title: Errata
Search URL Search Domain Scan URL
Title: Book Forum
Search URL Search Domain Scan URL
Title: Slideshare: How can I get started with Deep learning?
Search URL Search Domain Scan URL
Title: Article: Introducing Keras: deep learning with Python
Search URL Search Domain Scan URL
Title: Article: Deep Learning for Text
Search URL Search Domain Scan URL
Title: Source code on GitHub
Search URL Search Domain Scan URL
Title: Read in liveBook
Search URL Search Domain Scan URL
Title: 1. What is Deep Learning?
Search URL Search Domain Scan URL
Title: 1.1. Artificial intelligence, machine learning and deep learning
Search URL Search Domain Scan URL
Title: 1.1.1. Artificial intelligence
Search URL Search Domain Scan URL
Title: 1.1.2. Machine Learning
Search URL Search Domain Scan URL
Title: 1.1.3. Learning representations from data
Search URL Search Domain Scan URL
Title: 1.1.4. The "deep" in deep learning
Search URL Search Domain Scan URL
Title: 1.1.5. Understanding how deep learning works in three figures
Search URL Search Domain Scan URL
Title: 1.1.6. What deep learning has achieved so far
Search URL Search Domain Scan URL
Title: 1.1.7. Don’t believe the short-term hype
Search URL Search Domain Scan URL
Title: 1.1.8. The promise of AI
Search URL Search Domain Scan URL
Title: 1.2. Before deep learning: a brief history of machine learning
Search URL Search Domain Scan URL
Title: 1.2.1. Probabilistic modeling
Search URL Search Domain Scan URL
Title: 1.2.2. Early neural networks
Search URL Search Domain Scan URL
Title: 1.2.3. Kernel methods
Search URL Search Domain Scan URL
Title: 1.2.4. Decision trees, random forests, and gradient boosting machines
Search URL Search Domain Scan URL
Title: 1.2.5. Back to neural networks
Search URL Search Domain Scan URL
Title: 1.2.6. What makes deep learning different
Search URL Search Domain Scan URL
Title: 1.2.7. The modern machine-learning landscape
Search URL Search Domain Scan URL
Title: 1.3. Why deep learning, why now?
Search URL Search Domain Scan URL
Title: 1.3.1. Hardware
Search URL Search Domain Scan URL
Title: 1.3.2. Data
Search URL Search Domain Scan URL
Title: 1.3.3. Algorithms
Search URL Search Domain Scan URL
Title: 1.3.4. A new wave of investment
Search URL Search Domain Scan URL
Title: 1.3.5. The democratization of deep learning
Search URL Search Domain Scan URL
Title: 1.3.6. Will it last?
Search URL Search Domain Scan URL
Title: Read in liveBook
Search URL Search Domain Scan URL
Title: 2. Before we start: the mathematical blocks of neural networks
Search URL Search Domain Scan URL
Title: 2.1. A first look at a neural network
Search URL Search Domain Scan URL
Title: 2.2. Data representations for neural networks
Search URL Search Domain Scan URL
Title: 2.2.1. Scalars (0D tensors)
Search URL Search Domain Scan URL
Title: 2.2.2. Vectors (1D tensors)
Search URL Search Domain Scan URL
Title: 2.2.3. Matrices (2D tensors)
Search URL Search Domain Scan URL
Title: 2.2.4. 3D tensors and higher-dimensional tensors
Search URL Search Domain Scan URL
Title: 2.2.5. Key attributes
Search URL Search Domain Scan URL
Title: 2.2.6. Manipulating tensors in Numpy
Search URL Search Domain Scan URL
Title: 2.2.7. The notion of data batch
Search URL Search Domain Scan URL
Title: 2.2.8. Real-world examples of data tensors
Search URL Search Domain Scan URL
Title: 2.2.9. Vector data
Search URL Search Domain Scan URL
Title: 2.2.10. Timeseries data or sequence data
Search URL Search Domain Scan URL
Title: 2.2.11. Image data
Search URL Search Domain Scan URL
Title: 2.2.12. Video data
Search URL Search Domain Scan URL
Title: 2.3. The gears of neural networks: tensor operations
Search URL Search Domain Scan URL
Title: 2.3.1. Element-wise operations
Search URL Search Domain Scan URL
Title: 2.3.2. Broadcasting
Search URL Search Domain Scan URL
Title: 2.3.3. Tensor dot
Search URL Search Domain Scan URL
Title: 2.3.4. Tensor reshaping
Search URL Search Domain Scan URL
Title: 2.3.5. Geometric interpretation of tensor operations
Search URL Search Domain Scan URL
Title: 2.3.6. A geometric interpretation of deep learning
Search URL Search Domain Scan URL
Title: 2.4. The engine of neural networks: gradient-based optimization
Search URL Search Domain Scan URL
Title: 2.4.1. What's a derivative?
Search URL Search Domain Scan URL
Title: 2.4.2. Derivative of a tensor operation: the gradient
Search URL Search Domain Scan URL
Title: 2.4.3. Stochastic gradient descent
Search URL Search Domain Scan URL
Title: 2.4.4. Chaining derivatives: the backpropagation algorithm
Search URL Search Domain Scan URL
Title: 2.5. Looking back on our first example
Search URL Search Domain Scan URL
Title: Read in liveBook
Search URL Search Domain Scan URL
Title: 3. Getting started with neural networks
Search URL Search Domain Scan URL
Title: 3.1. Anatomy of a neural network
Search URL Search Domain Scan URL
Title: 3.1.1. Layers: the Lego bricks of deep learning
Search URL Search Domain Scan URL
Title: 3.1.2. Models: networks of layers
Search URL Search Domain Scan URL
Title: 3.1.3. Loss functions and optimizers: keys to configuring the learning process
Search URL Search Domain Scan URL
Title: 3.2. Introduction to Keras
Search URL Search Domain Scan URL
Title: 3.2.1. Keras, TensorFlow, Theano, and CNTK
Search URL Search Domain Scan URL
Title: 3.2.2. Developing with Keras: a quick overview
Search URL Search Domain Scan URL
Title: 3.3. Setting up a deep learning workstation
Search URL Search Domain Scan URL
Title: 3.3.1. Preliminary considerations
Search URL Search Domain Scan URL
Title: 3.3.2. Jupyter notebooks: the prefered way to run deep learning experiments
Search URL Search Domain Scan URL
Title: 3.3.3. Getting Keras running: two options
Search URL Search Domain Scan URL
Title: 3.3.4. Running deep learning jobs in the cloud: pros and cons
Search URL Search Domain Scan URL
Title: 3.3.5. What is the best GPU for deep learning?
Search URL Search Domain Scan URL
Title: 3.4. Classifying movie reviews: a binary classification example
Search URL Search Domain Scan URL
Title: 3.4.1. The IMDB dataset
Search URL Search Domain Scan URL
Title: 3.4.2. Preparing the data
Search URL Search Domain Scan URL
Title: 3.4.3. Building our network
Search URL Search Domain Scan URL
Title: 3.4.4. Validating our approach
Search URL Search Domain Scan URL
Title: 3.4.5. Using a trained network to generate predictions on new data
Search URL Search Domain Scan URL
Title: 3.4.6. Further experiments
Search URL Search Domain Scan URL
Title: 3.4.7. Wrapping up
Search URL Search Domain Scan URL
Title: 3.5. Classifying newswires: a multi-class classification example
Search URL Search Domain Scan URL
Title: 3.5.1. The Reuters dataset
Search URL Search Domain Scan URL
Title: 3.5.2. Preparing the data
Search URL Search Domain Scan URL
Title: 3.5.3. Building our network
Search URL Search Domain Scan URL
Title: 3.5.4. Validating our approach
Search URL Search Domain Scan URL
Title: 3.5.5. Generating predictions on new data
Search URL Search Domain Scan URL
Title: 3.5.6. A different way to handle the labels and the loss
Search URL Search Domain Scan URL
Title: 3.5.7. On the importance of having sufficiently large intermediate layers
Search URL Search Domain Scan URL
Title: 3.5.8. Further experiments
Search URL Search Domain Scan URL
Title: 3.5.9. Wrapping up
Search URL Search Domain Scan URL
Title: 3.6. Predicting house prices: a regression example
Search URL Search Domain Scan URL
Title: 3.6.1. The Boston Housing Price dataset
Search URL Search Domain Scan URL
Title: 3.6.2. Preparing the data
Search URL Search Domain Scan URL
Title: 3.6.3. Building our network
Search URL Search Domain Scan URL
Title: 3.6.4. Validating our approach using K-fold validation
Search URL Search Domain Scan URL
Title: 3.6.5. Wrapping up
Search URL Search Domain Scan URL
Title: Read in liveBook
Search URL Search Domain Scan URL
Title: 4. Fundamentals of machine learning
Search URL Search Domain Scan URL
Title: 4.1. Four different brands of machine learning
Search URL Search Domain Scan URL
Title: 4.1.1. Supervised learning
Search URL Search Domain Scan URL
Title: 4.1.2. Unsupervised learning
Search URL Search Domain Scan URL
Title: 4.1.3. Self-supervised learning
Search URL Search Domain Scan URL
Title: 4.1.4. Reinforcement learning
Search URL Search Domain Scan URL
Title: 4.2. Evaluating machine learning models
Search URL Search Domain Scan URL
Title: 4.2.1. Training, validation, and test sets
Search URL Search Domain Scan URL
Title: 4.2.2. Things to keep in mind
Search URL Search Domain Scan URL
Title: 4.3. Data preprocessing, feature engineering and feature learning
Search URL Search Domain Scan URL
Title: 4.3.1. Data preprocessing for neural networks
Search URL Search Domain Scan URL
Title: 4.3.2. Feature engineering
Search URL Search Domain Scan URL
Title: 4.4. Overfitting and underfitting
Search URL Search Domain Scan URL
Title: 4.4.1. Reducing the network size
Search URL Search Domain Scan URL
Title: 4.4.2. Adding weight regularization
Search URL Search Domain Scan URL
Title: 4.4.3. Adding dropout
Search URL Search Domain Scan URL
Title: 4.5. The universal workflow of machine learning
Search URL Search Domain Scan URL
Title: 4.5.1. Define the problem and assemble a dataset
Search URL Search Domain Scan URL
Title: 4.5.2. Pick a measure of success
Search URL Search Domain Scan URL
Title: 4.5.3. Decide on an evaluation protocol
Search URL Search Domain Scan URL
Title: 4.5.4. Prepare your data
Search URL Search Domain Scan URL
Title: 4.5.5. Develop a model that does better than a baseline
Search URL Search Domain Scan URL
Title: 4.5.6. Scale up: develop a model that overfits
Search URL Search Domain Scan URL
Title: 4.5.7. Regularize your model and tune your hyperparameters
Search URL Search Domain Scan URL
Title: Read in liveBook
Search URL Search Domain Scan URL
Title: 5. Deep learning for computer vision
Search URL Search Domain Scan URL
Title: 5.1. Introduction to convnets
Search URL Search Domain Scan URL
Title: 5.1.1. The convolution operation
Search URL Search Domain Scan URL
Title: 5.1.2. The max pooling operation
Search URL Search Domain Scan URL
Title: 5.2. Training a convnet from scratch on a small dataset
Search URL Search Domain Scan URL
Title: 5.2.1. The relevance of deep learning for small-data problems
Search URL Search Domain Scan URL
Title: 5.2.2. Downloading the data
Search URL Search Domain Scan URL
Title: 5.2.3. Building our network
Search URL Search Domain Scan URL
Title: 5.2.4. Data preprocessing
Search URL Search Domain Scan URL
Title: 5.2.5. Using data augmentation
Search URL Search Domain Scan URL
Title: 5.3. Using a pre-trained convnet
Search URL Search Domain Scan URL
Title: 5.3.1. Feature extraction
Search URL Search Domain Scan URL
Title: 5.3.2. Fine-tuning
Search URL Search Domain Scan URL
Title: 5.3.3. Wrapping up
Search URL Search Domain Scan URL
Title: 5.4. Visualizing what convnets learn
Search URL Search Domain Scan URL
Title: 5.4.1. Visualizing intermediate activations
Search URL Search Domain Scan URL
Title: 5.4.2. Visualizing convnet filters
Search URL Search Domain Scan URL
Title: 5.4.3. Visualizing heatmaps of class activation
Search URL Search Domain Scan URL
Title: Read in liveBook
Search URL Search Domain Scan URL
Title: 6. Deep learning for text and sequences
Search URL Search Domain Scan URL
Title: 6.1. Working with text data
Search URL Search Domain Scan URL
Title: 6.1.1. One-hot encoding of words or characters
Search URL Search Domain Scan URL
Title: 6.1.2. Using word embeddings
Search URL Search Domain Scan URL
Title: 6.1.3. Putting it all together: from raw text to word embeddings
Search URL Search Domain Scan URL
Title: 6.1.4. Wrapping up
Search URL Search Domain Scan URL
Title: 6.2. Understanding recurrent neural networks
Search URL Search Domain Scan URL
Title: 6.2.1. A first recurrent layer in Keras
Search URL Search Domain Scan URL
Title: 6.2.2. Understanding the LSTM and GRU layers
Search URL Search Domain Scan URL
Title: 6.2.3. A concrete LSTM example in Keras
Search URL Search Domain Scan URL
Title: 6.2.4. Wrapping up
Search URL Search Domain Scan URL
Title: 6.3. Advanced usage of recurrent neural networks
Search URL Search Domain Scan URL
Title: 6.3.1. A temperature forecasting problem
Search URL Search Domain Scan URL
Title: 6.3.2. Preparing the data
Search URL Search Domain Scan URL
Title: 6.3.3. A common sense, non-machine learning baseline
Search URL Search Domain Scan URL
Title: 6.3.4. A basic machine learning approach
Search URL Search Domain Scan URL
Title: 6.3.5. A first recurrent baseline
Search URL Search Domain Scan URL
Title: 6.3.6. Using recurrent dropout to fight overfitting
Search URL Search Domain Scan URL
Title: 6.3.7. Stacking recurrent layers
Search URL Search Domain Scan URL
Title: 6.3.8. Using bidirectional RNNs
Search URL Search Domain Scan URL
Title: 6.3.9. Going even further
Search URL Search Domain Scan URL
Title: 6.3.10. Wrapping up
Search URL Search Domain Scan URL
Title: 6.4. Sequence processing with convnets
Search URL Search Domain Scan URL
Title: 6.4.1. Understanding 1D convolution for sequence data
Search URL Search Domain Scan URL
Title: 6.4.2. 1D Pooling for sequence data
Search URL Search Domain Scan URL
Title: 6.4.3. Implementing a 1D convnet
Search URL Search Domain Scan URL
Title: 6.4.4. Combining CNNs and RNNs to process long sequences
Search URL Search Domain Scan URL
Title: 6.4.5. Wrapping up
Search URL Search Domain Scan URL
Title: Read in liveBook
Search URL Search Domain Scan URL
Title: 7. Advanced deep learning best practices
Search URL Search Domain Scan URL
Title: 7.1. Going beyond the Sequential model: the Keras functional API
Search URL Search Domain Scan URL
Title: 7.1.1. Introduction to the functional API
Search URL Search Domain Scan URL
Title: 7.1.2. Multi-input models
Search URL Search Domain Scan URL
Title: 7.1.3. Multi-output models
Search URL Search Domain Scan URL
Title: 7.1.4. Directed acyclic graphs of layers
Search URL Search Domain Scan URL
Title: 7.1.5. Layer weight sharing
Search URL Search Domain Scan URL
Title: 7.1.6. Models as layers
Search URL Search Domain Scan URL
Title: 7.1.7. Wrapping up
Search URL Search Domain Scan URL
Title: 7.2. Inspecting and monitoring deep learning models: using Keras callbacks and TensorBoard
Search URL Search Domain Scan URL
Title: 7.2.1. Using callbacks to act on a model during training
Search URL Search Domain Scan URL
Title: 7.2.2. Introduction to TensorBoard: the TensorFlow visualization framework
Search URL Search Domain Scan URL
Title: 7.2.3. Wrapping up
Search URL Search Domain Scan URL
Title: 7.3. Getting the most out of your models
Search URL Search Domain Scan URL
Title: 7.3.1. Advanced architecture patterns
Search URL Search Domain Scan URL
Title: 7.3.2. Hyperparameter optimization
Search URL Search Domain Scan URL
Title: 7.3.3. Model ensembling
Search URL Search Domain Scan URL
Title: 7.3.4. Wrapping up
Search URL Search Domain Scan URL
Title: Read in liveBook
Search URL Search Domain Scan URL
Title: 8. Generative deep learning
Search URL Search Domain Scan URL
Title: 8.1. Text generation with LSTM
Search URL Search Domain Scan URL
Title: 8.1.1. A brief history of generative recurrent networks
Search URL Search Domain Scan URL
Title: 8.1.2. How can we generate sequence data?
Search URL Search Domain Scan URL
Title: 8.1.3. The importance of the sampling strategy
Search URL Search Domain Scan URL
Title: 8.1.4. Implementing character-level LSTM text generation
Search URL Search Domain Scan URL
Title: 8.1.5. Wrapping up
Search URL Search Domain Scan URL
Title: 8.2. Deep Dream
Search URL Search Domain Scan URL
Title: 8.2.1. Implementing Deep Dream in Keras
Search URL Search Domain Scan URL
Title: 8.2.2. Wrapping up
Search URL Search Domain Scan URL
Title: 8.3. Neural style transfer
Search URL Search Domain Scan URL
Title: 8.3.1. The content loss
Search URL Search Domain Scan URL
Title: 8.3.2. The style loss
Search URL Search Domain Scan URL
Title: 8.3.3. Neural style transfer in Keras
Search URL Search Domain Scan URL
Title: 8.3.4. Wrapping up
Search URL Search Domain Scan URL
Title: 8.4. Generating images with Variational Autoencoders
Search URL Search Domain Scan URL
Title: 8.4.1. Sampling from latent spaces of images
Search URL Search Domain Scan URL
Title: 8.4.2. Concept vectors for image editing
Search URL Search Domain Scan URL
Title: 8.4.3. Variational autoencoders
Search URL Search Domain Scan URL
Title: 8.4.4. Wrapping up
Search URL Search Domain Scan URL
Title: 8.5. Introduction to generative adversarial networks
Search URL Search Domain Scan URL
Title: 8.5.1. A schematic GAN implementation
Search URL Search Domain Scan URL
Title: 8.5.2. A bag of tricks
Search URL Search Domain Scan URL
Title: 8.5.3. The generator
Search URL Search Domain Scan URL
Title: 8.5.4. The discriminator
Search URL Search Domain Scan URL
Title: 8.5.5. The adversarial network
Search URL Search Domain Scan URL
Title: 8.5.6. How to train your DCGAN
Search URL Search Domain Scan URL
Title: 8.5.7. Wrapping up
Search URL Search Domain Scan URL
Title: Read in liveBook
Search URL Search Domain Scan URL
Title: 9. Conclusions
Search URL Search Domain Scan URL
Title: 9.1. Key concepts in review
Search URL Search Domain Scan URL
Title: 9.1.1. Different brands of approaches to AI
Search URL Search Domain Scan URL
Title: 9.1.2. What makes deep learning special within machine learning
Search URL Search Domain Scan URL
Title: 9.1.3. How to think about deep learning
Search URL Search Domain Scan URL
Title: 9.1.4. Key enabling technologies
Search URL Search Domain Scan URL
Title: 9.1.5. The universal machine learning workflow
Search URL Search Domain Scan URL
Title: 9.1.6. Key network architectures
Search URL Search Domain Scan URL
Title: 9.1.7. The space of possibilities
Search URL Search Domain Scan URL
Title: 9.1.8. Mapping image data to vector data
Search URL Search Domain Scan URL
Title: 9.1.9. Mapping timeseries data to vector data
Search URL Search Domain Scan URL
Title: 9.2. The limitations of deep learning
Search URL Search Domain Scan URL
Title: 9.2.1. The risk of anthropomorphizing machine learning models
Search URL Search Domain Scan URL
Title: 9.2.2. Local generalization versus extreme generalization
Search URL Search Domain Scan URL
Title: 9.2.3. Take-aways
Search URL Search Domain Scan URL
Title: 9.3. The future of deep learning
Search URL Search Domain Scan URL
Title: 9.3.1. Models as programs
Search URL Search Domain Scan URL
Title: 9.3.2. Beyond backpropagation and differentiable layers
Search URL Search Domain Scan URL
Title: 9.3.3. Automated machine learning
Search URL Search Domain Scan URL
Title: 9.3.4. Lifelong learning and modular subroutine reuse
Search URL Search Domain Scan URL
Title: 9.3.5. In summary: the long-term vision
Search URL Search Domain Scan URL
Title: 9.4. Staying up to date in a fast-moving field
Search URL Search Domain Scan URL
Title: 9.4.1. Practice on real-world problems using Kaggle
Search URL Search Domain Scan URL
Title: 9.4.2. Read about the latest developments on Arxiv
Search URL Search Domain Scan URL
Title: 9.4.3. Explore the Keras ecosystem
Search URL Search Domain Scan URL
Title: 9.5. Final words
Search URL Search Domain Scan URL
Title: Read in liveBook
Search URL Search Domain Scan URL
Title: Appendix A: Installing Keras and its dependencies on Ubuntu
Search URL Search Domain Scan URL
Title: A.1. Installing the Python scientific suite
Search URL Search Domain Scan URL
Title: A.2. Setting up GPU support
Search URL Search Domain Scan URL
Title: A.3. Installing Theano (optional)
Search URL Search Domain Scan URL
Title: A.4. Installing Keras
Search URL Search Domain Scan URL
Title: Read in liveBook
Search URL Search Domain Scan URL
Title: Appendix B: Running Jupyter notebooks on an EC2 GPU instance
Search URL Search Domain Scan URL
Title: B.1. What are Jupyter notebooks? Why run Jupyter notebooks on AWS GPUs?
Search URL Search Domain Scan URL
Title: B.2. Why would you not want to use Jupyter on AWS for deep learning?
Search URL Search Domain Scan URL
Title: B.3. Setting up an AWS GPU instance
Search URL Search Domain Scan URL
Title: B.3.1. Configuring Jupyter
Search URL Search Domain Scan URL
Title: B.4. Installing Keras
Search URL Search Domain Scan URL
Title: B.5. Setting up local port forwarding
Search URL Search Domain Scan URL
Title: B.6. Using Jupyter from your local browser
Search URL Search Domain Scan URL
Page URL History
This captures the URL locations of the websites, including HTTP redirects and client-side redirects via JavaScript or Meta fields.
-
http://enews.manning.com/q/hY89T9cUICXUT0X2ixaVHnTE71v-T1wfaeAZcOJa2FpdGxpbi5wb3LdlbGxAY2FwaXRhbG9uZS5jb23DiAmx2c4NL2cY6XGRgnPAR3M58Vmg
HTTP 302
https://www.manning.com/books/deep-learning-with-python?trk_msg=1N7MRLO71AFK90KC22T57LIBMS&trk_contact=G9HFC3C7369KLN78RN71TFVR4C&trk_sid=AJ5TFHL416GMJT7TQRL9SLD7QC&utm_source=Listrak&utm_medium=Email&utm_term=https%3a%2f%2fwww.manning.com%2fbooks%2fdeep-learning-with-python&utm_campaign=Just+12+hours+left%e2%80%94Half+off+all+pBooks+TODAY+ONLY! Page URL
Redirected requests
There were HTTP redirect chains for the following requests:
Request Chain 24- https://www.google-analytics.com/r/collect?v=1&_v=j68&a=474260552&t=pageview&_s=1&dl=https%3A%2F%2Fwww.manning.com%2Fbooks%2Fdeep-learning-with-python%3Ftrk_msg%3D1N7MRLO71AFK90KC22T57LIBMS%26trk_contact%3DG9HFC3C7369KLN78RN71TFVR4C%26trk_sid%3DAJ5TFHL416GMJT7TQRL9SLD7QC%26utm_source%3DListrak%26utm_medium%3DEmail%26utm_term%3Dhttps%253a%252f%252fwww.manning.com%252fbooks%252fdeep-learning-with-python%26utm_campaign%3DJust%2B12%2Bhours%2Bleft%25e2%2580%2594Half%2Boff%2Ball%2BpBooks%2BTODAY%2BONLY!&ul=en-us&de=UTF-8&dt=Manning%20%7C%20Deep%20Learning%20with%20Python&sd=24-bit&sr=1600x1200&vp=1600x1200&je=0&_u=aGBAAEAL~&jid=231147788&gjid=1298210146&cid=1636607571.1533287095&tid=UA-5861300-1&_gid=1728406533.1533287095&_r=1>m=G7n59QHSR4&z=1815789507 HTTP 302
- https://stats.g.doubleclick.net/r/collect?v=1&aip=1&t=dc&_r=3&tid=UA-5861300-1&cid=1636607571.1533287095&jid=231147788&_gid=1728406533.1533287095&gjid=1298210146&_v=j68&z=1815789507
- https://www.manning.com/dashboard/userLoggedIn.json HTTP 302
- https://login.manning.com/cas/login?service=https%3A%2F%2Fwww.manning.com%2Flogin%2Fcas
- https://login.manning.com/cas/login?service=https%3A%2F%2Fwww.manning.com%2Flogin%2Fcas HTTP 302
- https://login.manning.com/login?service=https%3A%2F%2Fwww.manning.com%2Flogin%2Fcas
70 HTTP transactions
Method Protocol |
Resource Path |
Size x-fer |
Type MIME-Type |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
GET H/1.1 |
Primary Request
deep-learning-with-python
www.manning.com/books/ Redirect Chain
|
141 KB 141 KB |
Document
text/html |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
Redirect headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET S |
css
fonts.googleapis.com/ |
9 KB 902 B |
Stylesheet
text/css |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
application-61665f875da7a857e36801ae1773f7f2.css
www.manning.com/assets/ |
312 KB 46 KB |
Stylesheet
text/css |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
application-b51021e7811c13e728244a33ca2bd651.js
www.manning.com/assets/ |
706 KB 204 KB |
Script
application/javascript |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
logo-044c1fdfbef2b63064d6f4999d51f496.svg
www.manning.com/assets/ |
7 KB 3 KB |
Image
image/svg+xml |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET S |
gtm.js
www.googletagmanager.com/ |
73 KB 24 KB |
Script
application/javascript |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Chollet-DLP-HI.png
images.manning.com/270/360/resize/book/7/65fca1c-6826-472d-bbea-c1d4a7b3c570/ |
21 KB 22 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Jorgensen-PRS-MEAP-HI.png
images.manning.com/270/360/resize/book/d/9afa30f-fe28-4902-92da-908d7d5c0a36/ |
29 KB 29 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Trask_GDL_hires.png
images.manning.com/270/360/resize/book/a/2b99d49-847e-488c-ba6f-c919e0acb34e/ |
42 KB 42 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Richardson-MP-MEAP-HI.png
images.manning.com/270/360/resize/book/0/20bc554-2987-4b45-8823-8b030132b2b6/ |
29 KB 29 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Lane-NLP-MEAP-HI.png
images.manning.com/270/360/resize/book/7/aa010ef-60bc-4fd5-85ea-2080d0e5743c/ |
29 KB 29 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Luksa-Kubernetes-HI.png
images.manning.com/270/360/resize/book/d/c308a90-6ec2-4c20-8b57-087f9f9df05b/ |
21 KB 21 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Ceder-QPython-3ed-HI.png
images.manning.com/270/360/resize/book/9/afe7a0c-3fd0-4676-92ea-62d7cf929064/ |
25 KB 25 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Allaire-DLwithR-HI.png
images.manning.com/270/360/resize/book/a/4e5e97f-4e8d-4d97-a715-f6c2b0eb95f5/ |
23 KB 24 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Pumperla-DL-MEAP-HI.png
images.manning.com/270/360/resize/book/d/c47e2da-2192-4063-8058-b7b77e705749/ |
31 KB 31 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Brink-RWML-HI.png
images.manning.com/270/360/resize/book/3/2c4cc42-f154-428a-b6ca-2f94a69c1c47/ |
22 KB 23 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Shukla-MLTF-HI.png
images.manning.com/270/360/resize/book/d/848f767-1c05-470a-83f4-9ddabb67fdbd/ |
20 KB 20 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Bhargava-Algorithms_hires.png
images.manning.com/270/360/resize/book/3/0b325da-eb26-4e50-8a2a-46042c647083/ |
34 KB 34 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
fontawesome-all.min.css
www.manning.com/assets/ |
40 KB 10 KB |
Stylesheet
text/css |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET S |
trackjs.js
manning.postaffiliatepro.com/scripts/ |
31 KB 7 KB |
Script
application/javascript |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET S |
analytics.js
www.google-analytics.com/ |
34 KB 14 KB |
Script
text/javascript |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET S |
track.php
manning.postaffiliatepro.com/scripts/ |
19 B 292 B |
Script
application/x-javascript |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET S |
fbevents.js
connect.facebook.net/en_US/ |
43 KB 13 KB |
Script
application/x-javascript |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET S |
ec.js
www.google-analytics.com/plugins/ua/ |
3 KB 1 KB |
Script
text/javascript |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET S |
1940497162877014
connect.facebook.net/signals/config/ |
80 KB 16 KB |
Script
application/x-javascript |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET S |
collect
stats.g.doubleclick.net/r/ Redirect Chain
|
35 B 305 B |
Image
image/gif |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
Redirect headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET S |
/
www.facebook.com/tr/ |
44 B 297 B |
Image
image/gif |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
script.js
cdn.listrakbi.com/scripts/ |
154 KB 41 KB |
Script
text/javascript |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
character-a1b55ae6bb72a57ceb25832bc8f0ef91.png
www.manning.com/assets/ |
197 KB 197 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
squares-2-b35af8f88a2308304fb8ee53df1fcc8e.png
www.manning.com/assets/ |
5 KB 5 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Lato-Regular-3b9b99039cc0a98dd50c3cbfac57ccb2.ttf
www.manning.com/assets/lato/ |
642 KB 329 KB |
Font
font/ttf |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
fa-solid-900-8a8c0474283e0d9ef41743e5e486bf05.woff2
www.manning.com/assets/ |
49 KB 50 KB |
Font
font/woff2 |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
fa-regular-400-33f727ccde4b05c0ed143c5cd78cda0c.woff2
www.manning.com/assets/ |
12 KB 12 KB |
Font
font/woff2 |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
fa-brands-400-3654744dc6d6c37c9b3582b57622df5e.woff2
www.manning.com/assets/ |
60 KB 60 KB |
Font
font/woff2 |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET S |
S6u9w4BMUTPHh6UVSwiPGQ3q5d0.woff2
fonts.gstatic.com/s/lato/v14/ |
14 KB 14 KB |
Font
font/woff2 |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET S |
S6u8w4BMUTPHjxsAXC-qNiXg7Q.woff2
fonts.gstatic.com/s/lato/v14/ |
14 KB 15 KB |
Font
font/woff2 |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Cookie set
currentCartCount.json
www.manning.com/cart/ |
16 B 481 B |
XHR
application/json |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Cookie set
login
login.manning.com/cas/ Redirect Chain
|
0 -1 B |
XHR
|
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
Redirect headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
chevron-right-7fac3cb9dfbb692b85f08cd703a21faa.svg
www.manning.com/assets/ |
1 KB 1009 B |
Image
image/svg+xml |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
grainger.png
images.manning.com/720/960/resize/book/4/94b429f-1ac0-4702-9fa7-6001d01b9484/ |
105 KB 105 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Shukla-MLTF-HI.png
images.manning.com/720/960/resize/book/d/848f767-1c05-470a-83f4-9ddabb67fdbd/ |
93 KB 93 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Jorgensen-PRS-MEAP-HI.png
images.manning.com/720/960/resize/book/d/9afa30f-fe28-4902-92da-908d7d5c0a36/ |
133 KB 133 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Ceder-QPython-3ed-HI.png
images.manning.com/720/960/resize/book/9/afe7a0c-3fd0-4676-92ea-62d7cf929064/ |
133 KB 133 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
ingersoll.png
images.manning.com/720/960/resize/book/f/8e8518b-c796-445d-8f53-cba906cde357/ |
143 KB 143 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Pfeffer-PPP-HI.png
images.manning.com/720/960/resize/book/2/57c21ee-a252-4089-9b52-8d8d47b08dcc/ |
98 KB 99 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
chevron-left-99b6600c6ae3e60392fb49253c7d3ff9.svg
www.manning.com/assets/ |
1 KB 996 B |
Image
image/svg+xml |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Allaire-DLwithR-HI.png
images.manning.com/720/960/resize/book/a/4e5e97f-4e8d-4d97-a715-f6c2b0eb95f5/ |
115 KB 116 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Luksa-Kubernetes-HI.png
images.manning.com/720/960/resize/book/d/c308a90-6ec2-4c20-8b57-087f9f9df05b/ |
106 KB 107 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Lane-NLP-MEAP-HI.png
images.manning.com/720/960/resize/book/7/aa010ef-60bc-4fd5-85ea-2080d0e5743c/ |
125 KB 126 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
squares-liveAudio-4194eaabe17b8ae6ca8cab90fb88f2a8.svg
www.manning.com/assets/ |
75 KB 5 KB |
Image
image/svg+xml |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Chollet-DLP-HI.png
images.manning.com/720/960/resize/book/7/65fca1c-6826-472d-bbea-c1d4a7b3c570/ |
98 KB 98 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET S |
S6u9w4BMUTPHh7USSwiPGQ3q5d0.woff2
fonts.gstatic.com/s/lato/v14/ |
14 KB 14 KB |
Font
font/woff2 |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET S |
dFa5ZfeM_74wlPZtksIFYpEY6HOpW3pwfa0.woff2
fonts.gstatic.com/s/zillaslab/v3/ |
14 KB 14 KB |
Font
font/woff2 |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET S |
/
www.facebook.com/tr/ |
44 B 144 B |
Image
image/gif |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET S |
/
www.facebook.com/tr/ |
44 B 98 B |
Image
image/gif |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
OPTIONS H/1.1 |
login
login.manning.com/cas/ |
0 401 B |
XHR
text/plain |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
free-3a10dc61ed089b00c590e8c6e205d5e8.svg
www.manning.com/assets/ |
4 KB 2 KB |
Image
image/svg+xml |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
productsAutocompleteInfo
www.manning.com/api/search/ |
600 KB 601 KB |
XHR
application/json |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
getIds
s1.listrakbi.com/oSRPiytUPTkk/session/ |
175 B 1 KB |
Script
application/x-javascript |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
login
login.manning.com/ Redirect Chain
|
0 -1 B |
XHR
text/html |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
Redirect headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
animate.min.css
cdn.listrakbi.com/css/ |
5 KB 5 KB |
Stylesheet
text/css |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
CT.ashx
s1.listrakbi.com/t/ |
109 B 607 B |
Script
text/javascript |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
OPTIONS H/1.1 |
login
login.manning.com/ |
0 401 B |
XHR
text/plain |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Cookie set
login
login.manning.com/ |
258 KB 259 KB |
XHR
text/html |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Chollet-DLP-HI.png
images.manning.com/book/7/65fca1c-6826-472d-bbea-c1d4a7b3c570/ |
2 MB 2 MB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Pumperla-DL-MEAP-HI.png
images.manning.com/720/960/resize/book/d/c47e2da-2192-4063-8058-b7b77e705749/ |
112 KB 0 |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Richardson-MP-MEAP-HI.png
images.manning.com/720/960/resize/book/0/20bc554-2987-4b45-8823-8b030132b2b6/ |
120 KB 120 KB |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Bhargava-Algorithms_hires.png
images.manning.com/720/960/resize/book/3/0b325da-eb26-4e50-8a2a-46042c647083/ |
128 KB 0 |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Trask_GDL_hires.png
images.manning.com/720/960/resize/book/a/2b99d49-847e-488c-ba6f-c919e0acb34e/ |
128 KB 0 |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
GET H/1.1 |
Brink-RWML-HI.png
images.manning.com/720/960/resize/book/3/2c4cc42-f154-428a-b6ca-2f94a69c1c47/ |
32 KB 0 |
Image
image/png |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
General
Request headers
Response headers
|
Verdicts & Comments Add Verdict or Comment
107 JavaScript Global Variables
These are the non-standard "global" variables defined on the window object. These can be helpful in identifying possible client-side frameworks and code.
object| dataLayer object| google_tag_manager number| len string| GoogleAnalyticsObject function| ga object| PostAffTracker function| rpap function| setVisitor function| setAffiliate function| trackingFinished function| setAffiliateInfo function| papTrack function| PostAssoc function| PostAffAction function| PostAffAttributeWriter function| PostUrlReplacer function| PostValueReplacer function| PostAffCookieManager function| PostAffParams function| PostAffCookie function| PostAffRequest function| PostAffInfo function| PostAffTrackingRequest object| expired object| parameters object| scriptElement object| searchServerVars function| fbq function| _fbq object| gaplugins object| gaGlobal object| gaData string| biJsHost object| Search function| $ function| jQuery function| FlapDigit function| moment object| React object| core object| __core-js_shared__ function| _Utilities function| AsyncManager function| AsyncCall function| Identity function| LTK function| _Order function| _TRKT function| _Product function| _Customer function| _Client function| _Assembler function| _LTKClick function| _LTKSubscriber function| _Profile function| _ProfileItem function| _LTKSignup function| isWatermark function| SessionTracker function| SCAItem function| getCookieDomain function| _Session function| getItemData function| ltkYahoo function| mobileUserAgent function| Trigger function| EntryTrigger function| ExitTrigger function| ManualTrigger function| Action function| ListSubscriptionAction function| GetParameterByName function| HttpRequestGet function| GetHtmlFromQueryString function| Display function| Confirmation function| MobileDisplay function| MobileConfirmation function| Eligibility function| Metric function| ImpressionMetric function| SubmittedMetric function| CancelledMetric function| LTKModal string| _protocol object| _ltk_util object| match string| _ltkwmt object| _ltk undefined| customer_email undefined| customer_firstname undefined| customer_lastname undefined| order_id boolean| doOrderSubmit boolean| doCartSubmit number| _sti object| customEvent object| jQueryLoadCall number| _jQueryLoadInterval object| ltkLoadCall number| _ltkLoadInterval number| c_start string| ua object| matched object| browser object| lists number| c_end0 Cookies
Cookies are little pieces of information stored in the browser of a user. Whenever a user visits the site again, he will also send his cookie values, thus allowing the website to re-identify him even if he changed locations. This is how permanent logins work.
3 Console Messages
A page may trigger messages to the console to be logged. These are often error messages about being unable to load a resource or execute a piece of JavaScript. Sometimes they also provide insight into the technology behind a website.
Source | Level | URL Text |
---|
Security Headers
This page lists any security headers set by the main page. If you want to understand what these mean and how to use them, head on over to this page
Header | Value |
---|---|
Content-Security-Policy | frame-ancestors 'none' |
X-Frame-Options | Deny |
Indicators
This is a term in the security industry to describe indicators such as IPs, Domains, Hashes, etc. This does not imply that any of these indicate malicious activity.
cdn.listrakbi.com
connect.facebook.net
enews.manning.com
fonts.googleapis.com
fonts.gstatic.com
images.manning.com
login.manning.com
manning.postaffiliatepro.com
s1.listrakbi.com
stats.g.doubleclick.net
www.facebook.com
www.google-analytics.com
www.googletagmanager.com
www.manning.com
139.162.206.25
142.0.93.10
184.173.95.35
2a00:1450:4001:814::2008
2a00:1450:4001:814::200a
2a00:1450:4001:81d::2003
2a00:1450:4001:81d::200e
2a00:1450:400c:c00::9a
2a03:2880:f01c:8012:face:b00c:0:3
2a03:2880:f11c:8186:face:b00c:0:50fb
35.166.24.88
52.204.71.90
52.84.121.220
0100c264ee8403bb7767976dbbd4fceb5fc4709ecc54a7f579f58391ec6f93ea
03224d379c4cfe52622a4fdf7c46890ad291c8ec8ecf3ea6a291092f71b033a0
03cd8d5ae90bfde689e9dd11c185532a9c70038ccc18bcf6ac79357defd74e6e
048d83f116406487279a5de76da61bb457eeb9a0f7d5f4fffbb81a4828df6cc4
058ed961bfe422af7bfc65865f4c08531ec8ace995f8a1ec560a46581cb7712c
0b4c58a84fb3cbc1ac74c32deae992f00e897e95a1fca75f3ca0d4bb72dc9cc9
10d8d42d73a02ddb877101e72fbfa15a0ec820224d97cedee4cf92d571be5caa
155ef7601d4af029d8b6f3efa4ed4984748ea0a36c85f038f129ffdc6fb83b66
1b4c97a2809cdb53153139544e1f5db34e4917c8f01d2dd94cb9519e24e1ab3c
1d7b8b8116a7d47da17035c0f28f8c425e1ecd603a37807b9cf859bc0e9900f5
1ddd3b7b68a96da02979f972e4e9a8b6af63b5a17c75d7c7e0e3901d9f3a729c
22c1311d13d1852ef1eb8fd7fc8cb4566c636af8aff7135c16ad0a72982c38aa
2b67656b2a1ada4c1a7956ca88965fa0af7dc564a49a59b8beffff77bf39eafc
2c5fd41a9ed1bcd4a6b83af8aae58d89ac3a89207944fde111e997029a12facc
2dac5b9b2146141a521ad465efecb09da6da194450ec99a670bb89ca4949e867
2dd597426ab42d181450b338fd3baadd49deb32543dfcaec85676f2ab6d72d0a
30559317d9b0f866de8717db1fa2e3a34454f4b406ed73f8406a76248bbe9460
33e69b8a0e4388c828bb46e34b2cc65a654f796744255919f04bc2f905dbad8d
34a0afc93f1b611c938788eb0d90a8b13cf6efd779d9359b95bac78eec9de5ca
35f664fb604b00000a786acc6443cd755a38a4cf120b2b8a3496e759292f9803
383d34d51fce4be24d70ee96e43fa44f1adf438dc6f5aaf45edd7ae5c7906d50
3a9c12491656d737da63eda149480187732b770a7acb84f2f10f3a521aab16b2
3adeb12e77ca84758a396240fbb2c209f1dfc4b01d53c886b838b90b31f1ef7c
3fab1c883847e4b5a02f3749a9f4d9eab15cd4765873d3b2904a1a4c8755fba3
420e34b412983f786d1c9a3b97a1b9084a24dcb33d5495f0eb76957f6fd1c8dc
49127f3e663a03f3c794a1e7ca533a833563ae86fe7d44ad65140092162ac01b
581f1ccb5549b7c0a392d49837acdb4b8b1d247fc69ef39ab06c983f96b57794
5d7c184f73407fd0b6e92743095a0d2a5cb5d3b853ce898798c24ef87d622db1
6016a6ae710f704abdee8b86fac94279850816fb1bf586438be487c9511ec179
622aa050f0d004b41dd00cea283103050d88abf66b93503997aaad9c2cb44945
6532327f6ce4976a89d8f13d6f6084034c75aeeed1c84cc929852790375bc215
6ea957b7fb3beb2d6a166a82349141fa4da86b1e1a6f807d81c123989027513c
6f6940be0835c3ddec9199e5fc42be4cbc61ebcfd58c623fdf719366253f1780
8337212354871836e6763a41e615916c89bac5b3f1f0adf60ba43c7c806e1015
843135db886bd204f7caaf85d036dac1323f539e23a4d5e62f12296255298470
89994692bf65d9b975109229b568b8a634258f9022982bcc030b81db3b7a216e
935dacc408434ec39fd5cf85233f81b50b1a19c6f05c65028a93d9c453255581
9807c402cea30a75ac5d1e634e87a15f93d25b59a9e400763ced9967c8edaca0
99c93ff72dfa6070ce498c16b19a81d25e2d60990040e61c61d35dd96a6dfeac
9eb2dad118cfed112bb91a448d94a79c1fb21c877193aba4bd30e1fad97e9f8c
a3b3c4f67bf2b44294215e2be76f12794e6b142edec201e199c93c38739f2bfc
a84e52a11036ebedd14ed51131c476c0e8fcd278cc5805f69d51cd4730bfc2ef
a97ccd5da16b4f9a0658ef0fcc1876381bef60b881c1b008cf7f90edd4414b13
adb251fc7f9f6fc34be984b8d251e9f3a8e9a42e1dcea85bb15b6206d828740b
b6143b6b4d86918d18cd84b60ae0f37f74522fc145896a4f9645746070cb28d4
b6f13946d69138b670e74cecf6ade4082bf3cc907b0640cc46ea4e9dd2db057d
bb8fa5f5216fa65fb3b0cfc76de29efaf4e6ff82a281dc540fb568d4767f688e
be36257f43ede27d64f61dfbb1fe6cc8220854d03d5ebe60f4e8d104551773f0
c247dff8860aab8ad2a0f0b0005447f80bc057ead799d6bfe0538b789a3d9d7c
cbbca7d9888b4a9eab7d479756d2924f9b067fd38dab376797029df741f96ee4
cefb38bf2322e76ec911cf38f106879da405d9104a89de292bbd636e2495d483
d4381caa710b0003b2afd4e7b7d0f0860a5dd59a82c1348b72e60651263eb51c
d62f708a39f7b90c6138d0808afc399adb172c226cde4c53d148411fa5b472b6
d7b298cc86ecbb7b71787b54889c1ea92d94d7e144f049695bc89fa0425fe0e2
d8016e34cf33ad9dbafecba1afa2ac3ea83fd566ada4f7ee0000a07007d0cca5
db05855c2f667bf8d947c12c3eb1a6f1a9688f659680f53f3945ddd238094642
e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855
e786f03c66635de40ab6e733601ab08cc7a99b2cca969cd67caacb5028d7d859
f4351b2eeac0d637bb17ca78f4db08fb82dbcfcc7ab6b97ff190de98fad255cd
fdd225964ba7a0268bbe7353d34d91aac616b79e5bc2e5f55fb4ae9d24ebdc8f