Lists (7)
Stars
Scalable and user friendly neural 🧠 forecasting algorithms.
Lightning ⚡️ fast forecasting with statistical and econometric models.
Beta-RecSys: Build, Evaluate and Tune Automated Recommender Systems
Deepchecks: Tests for Continuous Validation of ML Models & Data. Deepchecks is a holistic open-source solution for all of your AI & ML validation needs, enabling to thoroughly test your data and mo…
The release of the Twitter algorithm, annotated for recsys
A python library for user-friendly forecasting and anomaly detection on time series.
A playbook for systematically maximizing the performance of deep learning models.
List of Computer Science courses with video lectures.
Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
Automatically visualize your pandas dataframe via a single print! 📊 💡
🎓 Path to a free self-taught education in Computer Science!
Learn ML engineering for free in 4 months!
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
Code repository for the O'Reilly publication "Building Machine Learning Pipelines" by Hannes Hapke & Catherine Nelson
Python library for converting Python calculations into rendered latex.
🎨 Diagram as Code for prototyping cloud system architectures
Hydra is a framework for elegantly configuring complex applications
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
Time series forecasting with PyTorch
A natural language modeling framework based on PyTorch
Roadmap to becoming an Artificial Intelligence Expert in 2022
The Incredible PyTorch: a curated list of tutorials, papers, projects, communities and more relating to PyTorch.
Data science interview questions and answers
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Repository containing notebooks of my posts on Medium
All Algorithms implemented in Python
Live training loss plot in Jupyter Notebook for Keras, PyTorch and others
此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。
A booklet on machine learning systems design with exercises. NOT the repo for the book "Designing Machine Learning Systems"