Starred repositories
💯 Curated coding interview preparation materials for busy software engineers
Explain complex systems using visuals and simple terms. Help you prepare for system design interviews.
Source code for Twitter's Recommendation Algorithm
Source code for Twitter's Recommendation Algorithm
✨ Innovative and open-source visualization application that transforms various data formats, such as JSON, YAML, XML, CSV and more, into interactive graphs.
Basic Discord app with examples
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning …
Code for the Kaggle Ensembling Guide Article on MLWave
Summaries and resources for Designing Machine Learning Systems book (Chip Huyen, O'Reilly 2022)
https://huyenchip.com/ml-interviews-book/
A library of reinforcement learning components and agents
An implementation of a deep learning recommendation model (DLRM)
TensorFlow Neural Machine Translation Tutorial
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
This is a repository for all workshop related materials.
A fault tolerant, protocol-agnostic RPC system
A scalable machine learning library on Apache Spark
DeText: A Deep Neural Text Understanding Framework for Ranking and Classification Tasks
A game theoretic approach to explain the output of any machine learning model.
Simple and Efficient Tensorflow implementations of NER models with tf.estimator and tf.data
OpenPose: Real-time multi-person keypoint detection library for body, face, hands, and foot estimation
A set of dockerfiles that provide Reinforcement Learning solutions for use in SageMaker.
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.
Tensors and Dynamic neural networks in Python with strong GPU acceleration
"Solving problems with Deep Learning: an in-depth example using PyTorch and its ecosystem" tutorial/lab
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