GRID: Generative Recommendation with Semantic IDs

Assignments for CS146S: The Modern Software Dev (Stanford University Fall 2025)

Semantic IDs: How to train an LLM-Recommender Hybrid with steerability and reasoning on recommendations.

Practical Machine Learning on Databricks, published by packt

Understanding Deep Learning - Simon J.D. Prince

Tips and resources to prepare for Behavioral interviews.

Code for the OOD Interview Book by ByteByteGo. Available on Amazon:

Files for my PyTorch book

LightLLM is a Python-based LLM (Large Language Model) inference and serving framework, notable for its lightweight design, easy scalability, and high-speed performance.

DCNv3: Towards Next Generation Deep Cross Network for Click-Through Rate Prediction

MuopDB - A Vector Database

LLM-based calorie tracker app

Official code repo for the O'Reilly Book - "Hands-On Large Language Models"

Super Repository for Coding Interview Preperation

A collection of research papers on Federated Recommender Systems.

nDCG and regret based tools to find value model weights

Site Reliability Engineer Interview Preparation Guide

👋 - The documentation for being an Artsy Engineer

O'Reilly book - Building Machine Learning Systems with a feature store: batch, real-time, and LLMs

System Design Studying can be daunting. This gives you a table to study different problems, understand what components they require, their pros and cons, and how to deal with mitigations.

A database of 450 Machine Learning (ML) system design case studies from 100+ companies.

This repository contains a curated collection of 300 case studies from over 80 companies, detailing practical applications and insights into machine learning (ML) system design. The contents are or…

Grandmaster-Level Chess Without Search

A project to deploy an online app that predicts the win probability for each NBA game every day. Demonstrates end-to-end Machine Learning deployment.

We show how to add a calibration arch to multi task multi-label models used in ranking of recommender systems

Files for my "Pandas Workout" book

Scalable Machine Learning and Deep Learning, Final Project, 2023/2024

A deep dive into embeddings starting from fundamentals

Solutions to all Meta/Facebook puzzles available on Meta's careers website (solutions in multiple languages)