towardsdatascience.com Open in urlscan Pro
162.159.152.4  Public Scan

Form analysis
0 forms found in the DOM

Text Content

Open in app

Sign In

Get started


Home
Notifications
Lists
Stories

--------------------------------------------------------------------------------

Write



631K Followers

Follow
Home
About
Editors' Picks
Features
Deep Dives
Grow
Contribute


RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

Maxime Labonne

·Pinned


THE PROGRAMMING PARADIGM TO FIND ONE SOLUTION AMONG 8,080,104 CANDIDATES

Introduction to Constraint Programming in Python with OR-tools — Constraint
Programming is a technique to find every solution that respects a set of
predefined constraints. It is an invaluable tool for data scientists to solve a
huge variety of problems, such as scheduling, timetabling, sequencing, etc. In
this article, we’ll see how to use CP in two different ways: …

Programming

8 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Zolzaya Luvsandorj

·Pinned


FROM ML MODEL TO ML PIPELINE

With Scikit-learn in Python — Building machine learning model is not only about
choosing the right algorithm and tuning its hyperparameters. Significant amount
of time is spent wrangling data and feature engineering before model
experimentation begins. These preprocessing steps can easily overwhelm your
worklflow and become hard to track. Focusing from ML model to ML…

Machine Learning

6 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Maya Murad

·Pinned


BACK TO BASICS: REVISITING THE RESPONSIBLE AI FRAMEWORK

Sifting through dozens of existing frameworks to create a robust mental model
for the responsible use and deployment of algorithmic decision-making systems —
In the last few months we have seen promising developments in establishing
safeguards for AI. This includes a landmark EU regulation proposal on AI that
prohibits unacceptable AI uses and imposes mandatory disclosures and evaluations
for high-risk systems, an algorithmic transparency standard launched by the UK
government, mandatory audits for…

Artificial Intelligence

9 min read






RESPONSES (1)



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Conor O'Sullivan

·Pinned


ANALYSING FAIRNESS IN MACHINE LEARNING (WITH PYTHON)

Doing an exploratory fairness analysis and measuring fairness using equal
opportunity, equalized odds and disparate impact — It is no longer enough to
build models that make accurate predictions. We also need to make sure that
those predictions are fair. Doing so will reduce the harm of biased predictions.
As a result, you will go a long way in building trust in your AI systems. …

Algorithm Fairness

19 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Iulia Turc

·Just now


WHY TEXT SUMMARIZATION IS STILL HARD

And how this poses an opportunity for startups — Out of all Natural Language
Processing (NLP) tasks, summarization is arguably one of the least
headline-worthy. Shrinking the content of an article is a lot less dazzling than
having GPT-3 automatically generate startup ideas. However, despite its
lower-key profile, text summarization is far from being solved, especially in
industry. The…

NLP

7 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Frank Andrade

·Just now


4 APPS THAT WILL MAKE YOU MORE PRODUCTIVE AS A DATA SCIENTIST

Become more productive when writing code, taking notes, organizing tasks,
projects, and more! — A data science workflow is full of tasks that need to be
done yesterday. If we add everyday office tasks such as going to meetings and
replying to emails, the list of things to do is endless. Fortunately, there are
apps that can help you become more productive and focus…

Data Science

5 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Christian Monson

·Just now


A.I. TALKS WITH ANIMALS

Can machine learning algorithms eavesdrop on animal language? — Captive
chimpanzees understand English as well as a human 2 year old¹¹ and use signs
from Human sign languages⁵. Dolphins jointly coordinate their actions to open
containers¹⁴ and perform novel tricks⁹. A parrot can reliably report the number
or color of an item¹⁰. …

Artificial Intelligence

10 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Michaël HOARAU

·Just now


YOUR ANOMALY DETECTION MODEL IS SMARTER THAN YOU THINK

Multivariate time series anomaly detection models can provide rich insights if
you invest some time in post-processing their results… — While dealing with
industrial sensor data, I often tackle anomaly detection use cases. I’ve been
working on this topic with dozens of customers in the past decade and almost
daily in the past five years. The typical end users I interact with are plant
managers, process engineers or operators on…

Time Series Analysis

13 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Sachin Date

·8 hours ago


WHAT HAPPENS WHEN YOU INCLUDE IRRELEVANT VARIABLES IN YOUR REGRESSION MODEL?

Your model looses precision. We’ll explain why. — In the previous article, we
saw how leaving out important variables causes the regression model’s
coefficients to become biased. In this article, we’ll look at the converse of
this situation namely, the damage caused to your regression model from stuffing
it with variables that are entirely superfluous. What are irrelevant and
superfluous variables?

Regression Analysis

10 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Kurtis Pykes

·8 hours ago


ALL YOU NEED TO KNOW ABOUT WRITING EFFECTIVE COMMENTS IN YOUR CODE

It’s as important as writing the source code — Comments are short,
programmer-readable explanations or annotations written directly into the source
code of a computer program. Although the computer ignores them while executing a
program, writing effective comments in your source code may be as important as
the actual code itself for the simple fact that software always remains…

Python

9 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Jason McEwen

·8 hours ago


EFFICIENT GENERALIZED SPHERICAL CNNS

Hybrid rotationally equivariant spherical CNNs — Notions of spherical
convolution offer a promising route to unlocking the potential of deep learning
for the variety of problems in which spherical data are prevalent. However, the
introduction of non-linearity is a challenge. In this post we explore how ideas
originating in quantum physics may be applied to overcome…

Machine Learning

10 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Jim Dowling

·9 hours ago


TESTING FEATURES WITH PYTEST

Testing feature logic, transformations, and feature pipelines with pytest —
TL;DR Operational machine learning requires the offline and online testing of
both features and models. In this article, we show you how to design, build, and
run test for features. The source code for the examples in this article are
available here on github. Introduction In 2020 in our MLOps with…

Pytest

14 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Frank Zickert | Quantum Machine Learning

·9 hours ago


TO REALLY “FOUL THINGS UP,” YOU NEED A COMPUTER — A QUANTUM COMPUTER

On the causes and effects of quantum errors — To err is human, but to really
foul things up you need a computer. Paul Ehrlich I am a software guy. Therefore,
it’s hard to admit that Paul Ehrlich certainly doesn’t refer to hardware but
software. Classical computers are fault-tolerant devices. They don’t err. These
computers need to distinguish between…

Quantum Computing

5 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Murtaza Ali

·9 hours ago


BREAKING DOWN THE POWERFUL MAGIC BEHIND THE PANDAS GROUPBY FUNCTION

A detailed explanation of how groupby works under the hood to help you
understand it better. — In recent years, some of the most popular data sets and
polls have been those surrounding governmental elections. Election season has
become a time of countless charts, maps, polls, and predictions making their way
through the popular media. I want you to imagine you wake up one hectic morning
and…

Data Science

7 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Ruben Winastwan

·9 hours ago


NAMED ENTITY RECOGNITION WITH BERT IN PYTORCH

How to leverage a pre-trained BERT model for custom data to predict the entity
of each word in a text — When it comes to dealing with NLP problems, BERT
oftentimes comes up as a machine learning model that we can count on in terms of
its performance. The fact that it’s been pre-trained on more than 2,500M words
and its bidirectional nature to learn information from a sequence of words…

Named Entity Recognition

11 min read






RESPONSES (1)



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Casey Cheng

·9 hours ago


14 WAYS TO OPTIMIZE BIGQUERY SQL

How to gain Ferrari speeds at Honda costs — Poorly optimized SQL queries are
like cracks on the lining of plumbing — barely keeping the water in. When the
water pressure is low, there are minor leaks but everything still works. The
nightmare begins when we amp up the load. The cracks, once negligible, now burst
wide open and…

Data Science

26 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Saul Dobilas

·9 hours ago


SPARSE AUTOENCODER NEURAL NETWORKS — HOW TO UTILISE SPARSITY FOR ROBUST
INFORMATION ENCODING

A comparison between Undercomplete and Sparse AE with a detailed Python example
— Intro Autoencoders enable us to distil information by utilising a neural
network architecture composed of an encoder and decoder. There are multiple
types of autoencoders that vary based on their structure or the problems they
are designed to solve. The four most commons ones are: Undercomplete Autoencoder
(AE) — the most…

Neural Networks

6 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Stefan Krawczyk

·10 hours ago


HOW TO ITERATE WITH HAMILTON IN A NOTEBOOK

For those that don’t know, Hamilton is a general purpose micro-framework for
specifying dataflows, e.g. specifying Pandas transforms. It helps you to
structure your code base, and improves your code, e.g. you always write unit
testable transform code with Hamilton. It does this by introducing a paradigm
where functions have…

Data Science

4 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Leah Simpson and Ray McLendon

·10 hours ago


WHAT’S THE BEST LANGUAGE FOR DATA SCIENCE?

The answer to this question is more nuanced than you may think — In a recent
group discussion, I found data scientists arguing over which machine learning
framework is better: PyTorch or TensorFlow. What I found funny is that I’ve
heard other versions of this debate countless times before. Python or R? MATLAB
or Mathematica? Windows or Linux? …

Python

7 min read






RESPONSES



What are your thoughts?

Cancel
Respond

Also publish to my profile

There are currently no responses for this story.

Be the first to respond.

--------------------------------------------------------------------------------

Jamshaid Shahir

·10 hours ago


DATA IMPUTATION WITH MAGIC

Abra-kadabra-alakazam! Eliminate noise in your data like MAGIC! — In single-cell
RNA sequencing data (scRNA-seq), which records the number of mRNA molecules
across the genome in individual cells, we frequently encounter low or zero
counts of these molecules. This is due to the sequencing machines’ low detection
efficiency of more sparsely-expressed genes, resulting in them being falsely
labeled as…

Denoising

8 min read





Get started

Sign In




Your home for data science. A Medium publication sharing concepts, ideas and
codes.

Follow

Connect with Towards Data Science




EDITORS


TDS EDITORS

Building the most vibrant data science community on the web. Share your insights
and projects with like-minded readers: bit.ly/write-for-tds

Follow


BEN HUBERMAN

Editor in Chief, Towards Data Science. Previously: Editorial lead, Automattic &
Senior Editor, Longreads.

Follow


CAITLIN KINDIG

Editor at Towards Data Science, she/her

Follow

See all


SIGN UP FOR THE VARIABLE


BY TOWARDS DATA SCIENCE

Every Thursday, the Variable delivers the very best of Towards Data Science:
from hands-on tutorials and cutting-edge research to original features you don't
want to miss. Take a look.

Get this newsletter

Help

Status

Writers

Blog

Careers

Privacy

Terms

About

Knowable

To make Medium work, we log user data. By using Medium, you agree to our Privacy
Policy, including cookie policy.