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Summaries and resources for Designing Machine Learning Systems book (Chip Huyen, O'Reilly 2022)
Recommendation Algorithm大规模推荐算法库，包含推荐系统经典及最新算法LR、Wide&Deep、DSSM、TDM、MIND、Word2Vec、Bert4Rec、DeepWalk、SSR、AITM，DSIN，SIGN，IPREC、GRU4Rec、Youtube_dnn、NCF、GNN、FM、FFM、DeepFM、DCN、DIN、DIEN、DLRM、MMOE、PLE、ESM…
[WIP] Resources for AI engineers. Also contains supporting materials for the book AI Engineering (Chip Huyen, 2025)
A logical, reasonably standardized, but flexible project structure for doing and sharing data science work.
PyTorch Lightning + Hydra. A very user-friendly template for ML experimentation. ⚡🔥⚡
Machine Learning Journal for Intermediate to Advanced Topics.
A simple template for Cybulde project
A best practice for deep learning project template architecture.
Pytorch Lightning code guideline for conferences
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. RAG systems combine information retrieval with generative models to provide accurate and cont…
A learning rate range test implementation in PyTorch
20+ high-performance LLMs with recipes to pretrain, finetune and deploy at scale.
Contains Company Wise Questions sorted based on Frequency and all time
Implementation of popular ML algorithms from scratch
Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep lear…
Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science
12 Weeks, 24 Lessons, AI for All!
Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
Materials for the Learn PyTorch for Deep Learning: Zero to Mastery course.
PyTorch Tutorial for Deep Learning Researchers
This repo contains my solutions to “Introduction to Machine Learning Interviews” by Chip Huyen.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials,…
Awesome LeetCode resources to learn Data Structures and Algorithms and prepare for Coding Interviews.