Towards Data Science

A Medium publication sharing concepts, ideas, and codes.

410,767 307 Followers
Ludovic Benistant

Editor at Towards Data Science

Amber Teng

A writer, learner, and explorer, Angela Teng spends most of her time thinking about how interdisciplinary collaboration can galvanize innovations in technology.

Anne Bonner

Secretly believes everyone should get involved with tech. Wants to help with that. Let’s connect on LinkedIn!

TDS Team

Sharing concepts, ideas, and codes. Learn more about us here:

Yenson Lau

ML Scientist at Layer 6 AI | Editor at Towards Data Science

Elliot Gunn

Data science publishing @ Towards Data Science. Previously @ C4ADS (data science intern), Global Strategy Lab (research fellow). Background in economics & ML.

Latest Posts

Introduction to Linear Algebra with NumPy

Basic concepts and operations with examples

Beginner’s Crash Course to Deep Learning and CNNs

An animated explanation with no complicated maths.

The Best Way to Generate Indices in BigQuery

Using GENERATE_ARRAY for Histograms and More

NumPy Crash Course: Array Basics

A data structure at the heart of nearly all data science tools.

Using Hourglass Networks To Understand Human Poses

A simple and digestible deep dive into the theory behind Hourglass Networks for human pose estimation

Thoughts on COVID-19 through data and deals

Examining through a tech-first lens, how coronavirus changed global consumer behaviour and product innovation forever.

Beyond Pandas: Spark, Dask, Vaex and other big data technologies battling head to head

API and performance comparison on a billion-rows dataset. What should you use?

Working with 3D data —  fastai2

Understanding fastai DataBlock and creating the building blocks to work with sequences of images for deep learning applications

5 Pro-Tips For Data Scientists To Write Good Code

The following advice is built from my experience moving from academia to working as a data scientist on a variety of projects across…

Machine Learning Algorithms. Here’s the End-to-End.

An end-to-end run-through of common algorithms; including random forest, multinomial Naive Bayes, logistic regression, kNN, and SVMs from…


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