The Best of Towards Data Science
20+ most popular Towards Data Science articles, as voted by our community.
Trending
These are currently making the rounds on Refind.
How to Learn Causal Inference on Your Own for Free
The ultimate self-study guide for all levels
Towards Data Science on Artificial Intelligence
Springer has released 65 Machine Learning and Data books for free
Hundreds of books are now free to download
Develop Your First AI Agent: Deep Q-Learning
Dive into the world of artificial intelligence — build a deep reinforcement learning gym from scratch.
Towards Data Science on Computer Vision
Object Detection with 10 lines of code
One of the important fields of Artificial Intelligence is Computer Vision. Computer Vision is the science of computers and software systems…
TensorFlow for Computer Vision — How to Implement Convolutions From Scratch in Python
You’ll need 10 minutes to implement convolutions with padding in Numpy
Towards Data Science on Data Science
Towards Data Science on Game Theory
Algorithmic Game Theory with Nashpy
Game Theory is a method of studying strategic situations. A ‘strategic’ situation is a setting where the outcomes which affect you depend…
Towards Data Science on GIS
Urban Logistics Network Simulation in Python
Building Anylogic’s GIS-Feature w/ SimPy, OSMnx and Leaflet.js
Creating Beautiful River Maps with Python
Forget GIS and analyse your Polygons, LineStrings and Points with Python
Towards Data Science on Machine Learning
Intuitively, How Do Neural Networks Work?
The term “Neural Networks” may seem mysterious, why is an algorithm called Neural Networks? Does it really mimic real neurons, and how?
Towards Data Science on Mlops
Design Patterns in Machine Learning for MLOps
Outlining some of the most common design patterns encountered when creating successful Machine Learning solutions
The Seven Stages of MLOps Maturity
A practical guide to building critical MLOps capabilities that maximize data science ROI
Towards Data Science on Python
9 One-Liners Anyone Learning Python Should Know
Make your Python code concise with these one-liners
Top 3 Python Functions You Don’t Know About (Probably)
Cleaner Code and Fewer Loops? Count me in.
Towards Data Science on Recommender Systems
A Simple Approach To Building a Recommendation System
Leveraging the Surprise package to build a collaborative filtering recommender in Python
Learning to Rank: A Complete Guide to Ranking using Machine Learning
Sorting items by relevance is crucial for information retrieval and recommender systems.
Towards Data Science on Tensorflow
A comprehensive introduction to Tensorflow's Sequential API and model for deep learning
Kickstart your understanding of one of Tensorflow’s most powerful set of tools for deep learning
Popular
These are some all-time favorites with Refind users.
Double Debiased Machine Learning, part 1 of 2
Causal inference, machine learning, and regularization bias
Mastering Prompt Engineering to Unleash ChatGPT’s Potential
Explore best practices and enhance your prompts for better results
Understand BLOOM, the Largest Open-Access AI, and Run It on Your Local Computer
See BLOOM in action solving math, translation, and coding problems.
6 SQL Tricks Every Data Scientist Should Know
SQL tricks to make your analytics work more efficient
If I had to start learning data science again, how would I do it?
A couple of days ago I started thinking if I had to start learning machine learning and data science all over again where would I start…
What is Refind?
Every day Refind picks the most relevant links from around the web for you. is one of more than 10k sources we monitor.
How does Refind curate?
It’s a mix of human and algorithmic curation, following a number of steps:
- We monitor 10k+ sources and 1k+ thought leaders on hundreds of topics—publications, blogs, news sites, newsletters, Substack, Medium, Twitter, etc.
- In addition, our users save links from around the web using our Save buttons and our extensions.
- Our algorithm processes 100k+ new links every day and uses external signals to find the most relevant ones, focusing on timeless pieces.
- Our community of active users gets the most relevant links every day, tailored to their interests. They provide feedback via implicit and explicit signals: open, read, listen, share, mark as read, read later, «More/less like this», etc.
- Our algorithm uses these internal signals to refine the selection.
- In addition, we have expert curators who manually curate niche topics.
The result: lists of the best and most useful articles on hundreds of topics.
How does Refind detect «timeless» pieces?
We focus on pieces with long shelf-lives—not news. We determine «timelessness» via a number of metrics, for example, the consumption pattern of links over time.
How many sources does Refind monitor?
We monitor 10k+ content sources on hundreds of topics—publications, blogs, news sites, newsletters, Substack, Medium, Twitter, etc.
Can I submit a link?
Indirectly, by using Refind and saving links from outside (e.g., via our extensions).
How can I report a problem?
When you’re logged-in, you can flag any link via the «More» (...) menu. You can also report problems via email to hello@refind.com
Who uses Refind?
450k+ smart people start their day with Refind. To learn something new. To get inspired. To move forward. Our apps have a 4.9/5 rating.
Is Refind free?
Yes, it’s free!
How can I sign up?
Head over to our homepage and sign up by email or with your Twitter or Google account.