Useful Links

Key RL Papers: Most influential papers in RL research.Ã°
Introduction to Reinforcement Learning: Excellent introduction to Reinforcement Learning
UCL Course in RL: Popular RL course given at University College London by David Silver.

Towards Model Explainability using SHAP: A new avenue in model explainability for ML models.
Maximum Likelihood and Maximum A Posterior Explained: Understanding these basic concepts in statistics.
The Data Science Lifecycle: Everything about DS projects.
Recipe for Training Neural Networks: Hands-on tips and tricks.
Colah’s Blog: Interesting machine learning blog with excellent visual explanations and intuitions.
Guide to Feature Extraction: Hitchhiker’s guide to feature extraction.
Predictive Maintenance Solutions: Predictive mainentance solutions from a Machine Learning perspective.
It’s not just p=0.048 vs. p=0.052: Another discussion about statistical significance.
Data Project Checklist: Data projects are much more than training an accurate model.
Neat Visualisations: Neat visualisations of important statistical concepts.

C++ Quiz: Fun C++ puzzles.
C++ Annotations: Excellent reference manual for the C++ programming language.
Teach Yourself to Program in 10 Years: Not everything happens overnight.
String Formatting in Python 3: Take advantage of the advanced string formatting techniques in Python 3.
The Missing Semester of Your CS Education: Short course to master essential productivity tools for programmers.
The Internals of PostgreSQL: Deep-dive into the internal of the database that everyone uses.

DeepL Translator: Best language translator.
Hacker News: Tech news.
Why Books Don’t Work: Argument why books are ineffective for absorbing knowledge.
100 Best Books of the 21th Century: Includes some of my favourite books.
Sapiens as a blog post: Relates to the link-above about why books don’t work. This is an excellent way to freshen up your memory of the book.