Stars
Creates diagrams from textual descriptions!
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its go…
Uplift modeling and causal inference with machine learning algorithms
Plugin to integrate Learning to Rank (aka machine learning for better relevance) with Elasticsearch
Visual tracking library based on PyTorch.
SymSpell: 1 million times faster spelling correction & fuzzy search through Symmetric Delete spelling correction algorithm
Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk
Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
oneAPI Deep Neural Network Library (oneDNN)
💎 Android application following best practices: Kotlin, Coroutines, JetPack, Clean Architecture, Feature Modules, Tests, MVVM, DI, Static Analysis...
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
High-level Deep Learning Framework written in Kotlin and inspired by Keras
Rich is a Python library for rich text and beautiful formatting in the terminal.
Rapid fuzzy string matching in Python using various string metrics
A time management utility for GNOME based on the pomodoro technique!
A minimal PyTorch re-implementation of the OpenAI GPT (Generative Pretrained Transformer) training
Streamlit — A faster way to build and share data apps.
A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning
Data validation using Python type hints
Stanford NLP Python library for tokenization, sentence segmentation, NER, and parsing of many human languages
Models and examples built with TensorFlow
An Open Source Machine Learning Framework for Everyone