Materials Science/Research

Beware of plausible predictions of fantasy materials

An interesting Nature article by Alex Zunger discussing the importance of stability and synthesis of digitally discovered materials.

Science Communication

The misuse of colour in science communication

Excellent article highlighting ways for the scientific community to identify and prevent the misuse of colour in science.

My Manuscript Was “Rejected without Review” from Chemistry of Materials: A Lesson in Burying the Lede

Useful article discussing how to become effective at scientific communication

Computer Science/Programming

Big-O Notation

Excellent introduction on Big-O notation - a way to characterize an algorithm’s efficiency in terms of execution time

What Does It Take To Be An Expert At Python?

Very informative PyData talk from James Powell.

Python Programming Tutorials

Nice Collection of YouTube videos on Python programming for beginners.

Data Science/Visualization

Seeing Theory

A visual introduction to probability and statistics

Clarity and Aesthetics in Data Visualization: Guidelines

Excellent article discussing the clarity and aesthetics in data visualization

Effective Pandas

Very useful talk on Pandas by Matt Harrison

Dimension reduction

Visualizing Data Using t-SNE

Wonderful talk by Laurens van der Maaten on how t-SNE works

BioTuring Webinar | Using t SNE for Data Analysis: A Quick Introduction | Laurens van der Maaten

Another informative talk by Laurens van der Maaten on using t-SNE for data analysis

Understanding UMAP

A nice article focused on the theory of UMAP, how to use it effectively, and how its performance compares with t-SNE.

Machine Learning

The First Rule of Machine Learning: Start without Machine Learning

A very useful article discussing the use of ML while starting with a new project

MLU-EXPLAIN: Visual explanations of core machine learning concepts

Machine Learning University (MLU) is an education initiative from Amazon designed to teach machine learning theory and practical application. As part of that goal, MLU-Explain exists to teach important machine learning concepts through visual essays in a fun, informative, and accessible manner.

Random Forests Algorithm explained with a real-life example and some Python code

A very informative article on Random Forest

GAMMA FACET

FACET is an open source library for human-explainable AI. It combines sophisticated model inspection and model-based simulation to enable better explanations of your supervised machine learning models

CausalNex

CausalNex is a Python library that uses Bayesian Networks to combine machine learning and domain expertise for causal reasoning. You can use CausalNex to uncover structural relationships in your data, learn complex distributions, and observe the effect of potential interventions

Why do tree-based models still outperform deep learning on tabular data?

Yes, it is still the case …

How to Use t-SNE Effectively

An interactive playground for t-SNE dimensionality reduction to help readers develop an intuition for technique and where it is best applied.

Comparing quantiles at scale in online A/B-testing

Calculate bootstrap confidence intervals for difference-in-quantiles in A/B tests with hundreds of millions of observations

Career and Job Search

Hiring Data Scientists With Intention

Nice article on reducing bias in hiring process for a Data Scientist position

Five Steps to Writing a Great Resume

Great tips on resume and cover letter