A Crash Course on Causality – Part 2
A guide to building robust decision-making systems in businesses with causal inference.
Daily Dose of Data Science
Every week, we share practical no-fluff deep dives on topics that truly matter to your skills for succeeding and staying relevant in ML & DS roles.
A Crash Course on Causality – Part 1
A guide to building robust decision-making systems in businesses with causal inference.
Implementing KANs From Scratch Using PyTorch
A step-by-step demonstration of an emerging neural network architecture — KANs.
A Beginner-friendly Introduction to Kolmogorov Arnold Networks (KAN)
What are KANs, how are they trained, and what makes them so powerful?
Implementing (Massively) Parallelized CUDA Programs From Scratch Using CUDA Programming
A beginner-friendly guide for curious minds who don't know the internal workings of model.cuda().
Understanding LoRA-derived Techniques for Optimal LLM Fine-tuning
LoRA-variants explained in a beginner-friendly way.
8 Fatal (Yet Non-obvious) Pitfalls and Cautionary Measures in Data Science
8 data science lesson I wish I had known earlier.
