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Open in app Sign up Sign In Write Sign up Sign In Heartbeat 11.8K Followers Follow Home About Data Science ML/DL MLOps Contribute Explore Comet Hritam Basak ·Just now SEMI-SUPERVISED DEEP LEARNING FOR MEDICAL IMAGE SEGMENTATION The past few years have witnessed exponential growth in medical image analysis using deep learning. Be it stroke detection from brain MRIs, melanoma detection, robotic surgery, etc., medical image segmentation has always been the cornerstone of these applications [1]. In this article we will look into medical image segmentation and… Medical Image Analysis 18 min read Medical Image Analysis 18 min read -------------------------------------------------------------------------------- Barakarandy ·1 day ago THE FUTURE OF MACHINE LEARNING: UNDERSTANDING GANS AND DRL Deep learning has grown in importance as a focus of artificial intelligence research and development in recent years. Deep Reinforcement Learning (DRL) and Generative Adversarial Networks (GANs) are two promising deep learning trends. Below are some of the most promising use cases for DRL and GANs: DRL: Robotics: DRL algorithms… Deep Learning 8 min read Deep Learning 8 min read -------------------------------------------------------------------------------- Timothy Lu ·5 days ago A DETAILED BEGINNER’S GUIDE TO KERAS TUNER Introduction Have you ever wondered how to use Bayesian optimization with TensorFlow? Curious how to design your deep neural networks’ depth and shape? Well, here’s the guide for you. A big part of data science is tuning our models and improving upon them over time. But instead of just tuning specific… Keras 10 min read Keras 10 min read -------------------------------------------------------------------------------- Edwin Maina ·5 days ago USING DEEP LEARNING TO IMPROVE THE TRADITIONAL MACHINE LEARNING PERFORMANCE Deep learning for feature extraction, ensemble models, and more — The advent of deep learning has been a game-changer in machine learning, paving the way for the creation of complex models capable of feats previously thought impossible. These models have been used to achieve state-of-the-art performance in many different fields, including image classification, natural language processing, and speech recognition. This… Deep Learning 7 min read Deep Learning 7 min read -------------------------------------------------------------------------------- Jammie sandy ·Feb 21 SENTIMENT ANALYSIS WITH SPARKNLP AND COMET Introduction Sentiment analysis is a natural language processing technique which identifies and extracts subjective information from source materials using computational linguistics and text analysis. It is employed to ascertain a speaker’s or writer’s feelings, attitudes, and opinions with regard to a particular subject or general contextual polarity of a work. Applications… Comet 6 min read Comet 6 min read -------------------------------------------------------------------------------- Mwanikii ·Feb 20 AN END-TO-END GUIDE ON USING COMET ML’S MODEL VERSIONING FEATURE: PART 1 First-time project and model registration — The world of machine learning and data science is awash with technicalities. With each passing day, it becomes ever more evident that a practitioner in this field needs to keep track of a lot of things lest they fall into the deluge of complexity. Fortunately, there are many workarounds to… Comet 7 min read Comet 7 min read -------------------------------------------------------------------------------- Klurdy Studios ·Feb 15 TEXT CLASSIFICATION USING R, KERAS, AND COMET ML Text classification is an interesting application of natural language processing. It is a supervised learning methodology that predicts if a piece of text belongs to one category or the other. As a machine learning engineer, you start with a labeled data set that has vast amounts of text that have… NLP 6 min read NLP 6 min read -------------------------------------------------------------------------------- Omale Happiness ·Feb 14 TRANSFORMING A HORSE TO A ZEBRA USING A GENERATIVE ADVERSARIAL NETWORK (GAN) Introduction When two deep learning models work together in the style of a zero-sum game, one agent’s gain is another agent’s loss. This is known as a generative adversarial network (GAN). With a training set as its starting point, this approach learns to generate new data with the same statistics as… Gans 6 min read Gans 6 min read -------------------------------------------------------------------------------- Pranjal Saxena ·Feb 13 THINGS YOU CAN DO USING KANGAS LIBRARY IN DATA SCIENCE In-depth Analysis of Kangas Library using Python — Working with large datasets has always been a challenge for data developers, and it remains so in the current data industry. One of the main issues developers face is how to efficiently handle and process massive volumes of multimedia data, such as images. However, technological advances have led to the… Kangas 7 min read Kangas 7 min read -------------------------------------------------------------------------------- Khushboo kumari ·Feb 9 NATURAL LANGUAGE PROCESSING WITH SPACY (A PYTHON LIBRARY) Introduction Natural language processing (NLP) is the field that gives computers the ability to recognize human languages, and it connects humans with computers. One can build NLP projects in different ways, and one of those is by using the Python library SpaCy. This post will go over how the most cutting-edge… Spacy 6 min read Spacy 6 min read -------------------------------------------------------------------------------- Daniel Tope Omole ·Feb 8 NATURAL LANGUAGE PROCESSING WITH R The field of natural language processing (NLP), which studies how computer science and human communication interact, is rapidly growing. By enabling robots to comprehend, interpret, and produce natural language, NLP opens up a world of research and application possibilities. The first section of this article will look at the various… Heartbeat 12 min read Heartbeat 12 min read -------------------------------------------------------------------------------- Jammie sandy ·Feb 7 UNDERSTANDING LANGUAGE MODELS IN NLP Understanding the concept of language models in natural language processing (NLP) is very important to anyone working in the Deep learning and machine learning space. They are essential to a variety of NLP activities, including speech recognition, machine translation, and text summarization. Language models can be divided into two categories: … Large Language Models 5 min read Large Language Models 5 min read -------------------------------------------------------------------------------- İrem Kömürcü ·Feb 6 FIRST STEP TO OBJECT DETECTION ALGORITHMS Object detection is a field of computer vision used to identify and position objects within an image. Examples of object detection applications include detecting abnormal movement from security cameras, obstacle detection in autonomous driving, and character detection from within a document. How do Object Detection Algorithms Work? There are two main categories of object detection algorithms. … Object Detection 7 min read Object Detection 7 min read -------------------------------------------------------------------------------- Tioluwanioyedele ·Feb 1 PRINCIPLES OF MLOPS Machine learning has become an essential part of our lives because we interact with various applications of ML models, whether consciously or unconsciously. Machine Learning Operations (MLOps) are the aspects of ML that deal with the creation and advancement of these models. In this article, we’ll learn everything there is… Mlops 6 min read Mlops 6 min read -------------------------------------------------------------------------------- Pralabh Saxena ·Jan 31 GUIDE TO NON-LINEAR ACTIVATION FUNCTIONS IN DEEP LEARNING Non-linear activation functions that you need to know — Activation functions are equations or mathematical formulas that help us determine the output of a neural network. The main purpose of an activation function is to derive an output value based on the input value that is fed to a neuron. In deep learning, activation functions add non-linearity to the… Activation Functions 7 min read Activation Functions 7 min read -------------------------------------------------------------------------------- Oluseye Jeremiah ·Jan 30 TRACKING YOUR SENTIMENT ANALYSIS WITH COMET Sentiment analysis, commonly referred to as “opinion mining,” is the method of drawing out irrational information from written or spoken words. The study of how people communicate their thoughts, beliefs, and feelings through language is a fast-expanding area of natural language processing (NLP). Customer service, marketing, and political analysis are… Heartbeat 8 min read Heartbeat 8 min read -------------------------------------------------------------------------------- Loyford Mwenda ·Jan 26 N-GRAMS AND HOW TO IMPLEMENT THEM WITH THE PYTHON NLTK LIBRARY Understanding and creating N-grams for Natural Language Processing (NLP) with Python NLTK library — In Natural Language Processing (NLP), we train models to enable computers to understand text and spoken words in the same way humans can. … NLP 9 min read NLP 9 min read -------------------------------------------------------------------------------- Gourav Bais ·Jan 25 SENTIMENT ANALYSIS WITH PYTHON AND STREAMLIT Build and deploy your own sentiment classification app using Python and Streamlit — Nowadays, working on tabular data is not the only thing in Machine Learning (ML). Data formats like image, video, text, etc., are getting famous with use cases like image classification, object detection, chat-bots, text generation, and more. One such popular use case is sentiment analysis, the process of determining whether… Sentiment Analysis 15 min read Sentiment Analysis 15 min read -------------------------------------------------------------------------------- Felix Gutierrez ·Jan 25 CONSTRUCTING AND VISUALIZING DATAGRIDS IN KANGAS A comprehensive introductory tutorial on how to create your Datagrids and then manipulate, classify, and visualize in Kangas UI — Introduction Kangas is a tool developed by Comet that is still in the beta phase but is open-source and free to use for everyone. It’s defined as a tool for exploring, analyzing, and visualizing large-scale multimedia data. According to its GitHub page: The key features of Kangas include: Datagrid 3 min read Datagrid 3 min read -------------------------------------------------------------------------------- Mwanikii ·Jan 24 TRAINING GRADIENT BOOSTING MODELS WITH COMET ML Guide for programmers with Optuna experience — Introduction Hyperparameters are among the most important aspects of any given model in Data Science and Machine Learning applications. The right combination of hyperparameters is essential when one desires to come up with a great model. A pertinent problem that plagues engineers and coders is the fact that it is difficult… Hyperparameter Tuning 7 min read Hyperparameter Tuning 7 min read Comet is a machine learning platform helping data scientists, ML engineers, and deep learning engineers build better models faster Follow Connect with Heartbeat EDITORS EMILIE LEWIS Content and Community Manager @ Comet Follow GIDEON MENDELS Co-founder/CEO of Comet.ml — a machine learning experimentation platform helping data scientists track, compare, explain, reproduce ML experiments. Follow THALES CEOLIN Follow See all SIGN UP FOR THE HEARTBEAT NEWSLETTER BY HEARTBEAT Exploring the latest in MLOps, Deep Learning, and Data Science Take a look. By signing up, you will create a Medium account if you don’t already have one. Review our Privacy Policy for more information about our privacy practices. Get this newsletter Help Status Writers Blog Careers Privacy Terms About Text to speech To make Medium work, we log user data. 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