Library | हृषीकेश सिंह

“Humans are obsessed with escapism through movies, books, music, art, daydreams, our souls weren’t made for this world.”

– Read somewhere, I don’t remember 💭

Only keeping the fleeting flairs of these pieces.

Why do you read?

Because it takes me across space and time.

Philosophers a thousand years dead have shared their thoughts with me. I have watched over Heyerdahl's shoulder as he navigated the South seas on a raft. I've saved Fantastica with a wish, survived triffids and hunted the white whale.

Books take me places no train or plane ever will.

Books: Non-Fiction

1984

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Iliad

Ready to Fire

Blindness

The Trail

Odyssey

Eichmann in Jerusalem

I have read the work of German philosopher Hannah Arendt in the past and the Eichmann trial came up frequently but I read this book after watching the movie Operation Finale and a documentary The Specialist: Portrait of a Modern Criminal.

Prana and Pranayama

An exceptional book by Swami Niranjanananda Saraswati which everyone should read since everyone breaths. I never knew I was breathing wrong. This book will make you understand the deep correlation between your prana and your holistic well being. I found this book accidently when I was visiting a monestary (मठ)

The Trail

example image — Energy and Civilization: A History (Vaclav Smil)

Books: Fiction

Learning Resources

NLP

This is an unstructured list of resources for learning NLP a.k.a. Natural Language Processing, ranging from basics to advanced in not so particular order.

A visual introduction to layman verison of Generative AI: This is an interactive article to explain the simplified innner working of LLM.
Large Language Models: A Survey: A review paper presenting a comprehensive overview of LLMs. Weekend reading stuff.
Machine Learning Engineering Open Book: Assimilation of really valuable guidance. All you need to actually build real world application in production.

Reinforcement Learning

DeepMind:
- Instructor: David Silver
- Even though the course is a little older(2013) but the explanations are completely on point and intuitive with a perfect balance of mathematics and visual explanation. David Silver for reinforcement learning is like Andrew Ng for classical machine learning.

Got recommendations? Drop me a note!