Engineering Best Practices
Implementing 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().
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Engineering Best Practices
8 Fatal (Yet Non-obvious) Pitfalls and Cautionary Measures in Data Science
8 data science lesson I wish I had known earlier.
Classical ML and Deep Learning
15 Ways to Optimize Neural Network Training (With Implementation)
Techniques that help you become a "machine learning engineer" from a "machine learning model developer."
Classical ML and Deep Learning
A Detailed and Beginner-Friendly Introduction to PyTorch Lightning: The Supercharged PyTorch
Immensely simplify deep learning model building with PyTorch Lightning.
LLM and Fine-tuning
Augmenting LLMs: Fine-Tuning or RAG?
Understanding the tradeoffs between RAG and Fine-tuning, and owning the model vs. using a third-party host.
LLM and Fine-tuning
Implementing DoRA (an Improved LoRA) from Scratch
A powerful LoRA-variant explained in a beginner-friendly way and implemented in PyTorch.
LLM and Fine-tuning
Understanding LoRA-derived Techniques for Optimal LLM Fine-tuning
LoRA-variants explained in a beginner-friendly way.
LLM and Fine-tuning
Implementing LoRA From Scratch for Fine-tuning LLMs
Understanding the challenges of traditional fine-tuning and addressing them with LoRA.
