My Blogs
Technical notes on machine learning, language systems, computer systems, and research.
how do keyword spotting models work?
a guide to keyword spotting, audio features, neural networks, training, and continuous detection
how does dynamic memory allocation work?
a guide to dynamic memory allocation, the heap, malloc, free, and allocator internals
how does interprocess communication work?
a guide to inter-process communication, pipes, message queues, shared memory, and synchronization
How does virtual memory even work?
a guide to virtual memory, page tables, TLBs, page faults, and copy-on-write
Wait, what's KL Divergence
A practical exploration of KL divergence using hospital emergency room wait times, comparing normal and exponential distributions to find the best model for real-world data.
how do i train translation models on low-resource languages?
a guide into how to train translation models on low-resource languages
Enhance Your Model - 1 [Week 9]
a guide into how lora, model distillation, gradient clipping and early stopping work
LLMs - 1 [Week 8]
a guide into how embeddings, positional embeddings, tokenizer (especially bpe tokenizer) work
Basics of NLP - 3 [Week 7]
a guide into how hidden markov models, text clustering, attention work
Basics of NLP - 2 [Week 6]
discussion into how pos tagging, ner, sentiment analysis, and n-gram models work
Basics of NLP - 1 [Week 5]
discussion into how text preprocessing, regex, frequencies, and word embeddings work
RNNs [Week 4]
a deep dive into recurrent neural networks and how the math behind it works
Transformers [Week 2]
a deep dive into transformers and a visual guide into how it works
Linear Regression: A Gentle Introduction
An intuitive introduction to linear regression, including foundations, assumptions, and solutions with gradient descent and closed-form methods.
System Design, Visually
A 63-slide visual walkthrough of the building blocks behind reliable systems.