Nikisha

LLMs || Machine Learning || NLP || Generative AI

[Nikisha @k_nikisha]

@cneuralnetwork That's a dream to work in research, but disheartened.

[Nikisha @k_nikisha]

@e_opore Hiiiiiiiiiiiiiiiii 👋

[Nikisha @k_nikisha]

@cneuralnetwork Let's go!!

[neural nets. @cneuralnetwork]

launching today

let's try to solve the research problems in india!

[neural nets. @cneuralnetwork]

to be good at something , you must break your body minutely cell by cell
you did at your prime

[Nikisha @k_nikisha]

@cneuralnetwork Ashley, look at me ! 🔥🔥🔥

[Nikisha @k_nikisha]

@TakSec @wunderwuzzi23 @0din @Hacker0x01 @Bugcrowd @metabugbounty Yes pls!!!

[Nikisha @k_nikisha]

@0xratnakar Thanks man ! 😄

[Nikisha @k_nikisha]

@electro_pppp That does look delicious 😋

[Nikisha @k_nikisha]

@cneuralnetwork @electro_pppp Congratulations @electro_pppp 🥳🥳!

So how many parties are pending ?? 😜

[Nikisha @k_nikisha]

@cneuralnetwork You’re doing an excellent job, keep growing and stay happy! :-)

[Nikisha @k_nikisha]

@cneuralnetwork Congratulations 👏👏!!
All the best on this journey

[Nikisha @k_nikisha]

@soumilrathi Context 🔥

[Ihtesham Ali @ihtesham2005]

Say goodbye to paying $200 for AI textbooks that skip the intuition and leave you more confused than when you started.

An AI engineer spent years filling notebooks with first-principles explanations of maths, computing, and AI the kind that build real understanding instead of just getting you through an exam.

In 2025, he shared those notes with a few friends preparing for interviews at DeepMind, OpenAI, and Nvidia. They all got in, and they all perform well in their roles today.

Now he has open-sourced the entire thing as a free, unconventional textbook called the Maths, CS & AI Compendium, covering 18 chapters from vectors and calculus all the way through GPU programming, inference optimization, quantum ML, and AI for biology.

The six foundational chapters are live right now, covering vectors, matrices, calculus, statistics, probability, and machine learning with the kind of intuition-first writing that most academic textbooks never bother to include.

The remaining chapters on transformers, computer vision, audio, multimodal learning, autonomous systems, CUDA, systems design, and edge inference are coming next.

The notes that opened doors at the best AI labs in the world are now free for every curious practitioner on the internet.

Apache 2.0 License. 100% Open Source.

[Nikisha @k_nikisha]

@nishant_py Hi

[abhinav @AbhinavXJ]

Dear algorithm, show this to only those competent people who have cleared this mission

[neural nets. @cneuralnetwork]

midsems this week.

[GitHub Projects Community @GithubProjects]

An Open Source Python alternative to NotebookLM's podcast feature