LLMs
Prompting vs. RAG vs. Fine-tuning
Which one is best for you?
Deep Learning
A collection of 15 posts
LLMs
From PyTorch to Lightning Fabric
Scale model training with 4 small changes.
LLM and Fine-tuning
AugSBERT: Bi-encoders + Cross-encoders for Sentence Pair Similarity Scoring – Part 2
A deep dive into extensions of cross-encoders and bi-encoders for sentence pair similarity.
LLM and Fine-tuning
Bi-encoders and Cross-encoders for Sentence Pair Similarity Scoring (Part 1)
A deep dive into why BERT isn't effective for sentence similarity and advancements that shaped this task forever.
Classical ML and Deep Learning
Model Interpretability (Part 1)
A deep dive into PDPs and ICE plots, along with their intuition, considerations, how to avoid being misled, and code.
Graph ML Course
Graph Neural Networks Part 3 (Implementation Included)
A practical and beginner-friendly guide to building neural networks on graph data.
Graph ML Course
Graph Neural Networks Part 2 (Implementation Included)
A practical and beginner-friendly guide to building neural networks on graph data.
Graph ML Course
Graph Neural Networks Part 1 (Implementation Included)
A practical and beginner-friendly guide to building neural networks on graph data.
Deep Learning
All-Reduce and Ring-Reduce for Model Synchronization in Multi-GPU Training
Two synchronization algorithms for intermediate-ML models.
Engineering Best Practices
A Beginner-friendly Guide to Multi-GPU Model Training
Models are becoming bigger and bigger. Learn how to scale models using distributed training.
Classical ML and Deep Learning
Implementing KANs From Scratch Using PyTorch
A step-by-step demonstration of an emerging neural network architecture — KANs.
Classical ML and Deep Learning
A Beginner-friendly Introduction to Kolmogorov Arnold Networks (KAN)
What are KANs, how are they trained, and what makes them so powerful?
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().
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.
