Friendly machine learning for the web! 🤖

Short JavaScript code snippets for all your development needs

🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models

Keras Implementation of Faster R-CNN

Python implementation of a Simulated Bifurcation (SB) algorithm in order to solve optimal asset allocations for a portfolio or other Ising problems.

Public repo for DeepLearning.AI MLEP Specialization

Algorithms for explaining machine learning models

Solvers/annealers for simulated quantum annealing on CPU and CUDA(NVIDIA GPU).

Generative Models by Stability AI

🏆 A ranked gallery of awesome streamlit apps built by the community

Python package for exploratory text data analysis

An implementation of Microsoft's "FastSpeech 2: Fast and High-Quality End-to-End Text to Speech"

Community maintained fork of pdfminer - we fathom PDF

Hands-on Exploratory Data Analysis with Python, published by Packt

Sentiment Analysis, Text Classification, Text Augmentation, RNA Sequence Classification, Sequence Regression Model, Text Adversarial defense, etc.; 细粒度情感分析，文本分类，文本增强，RNA分类，序列回归，文本对抗防御等等

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

Intel(R) Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application

Hummingbird compiles trained ML models into tensor computation for faster inference.

scikit-learn_bench benchmarks various implementations of machine learning algorithms across data analytics frameworks. It currently support the scikit-learn, DAAL4PY, cuML, and XGBoost frameworks f…

cuML - RAPIDS Machine Learning Library

The fastai deep learning library

Evaluate and monitor ML models from validation to production. Join our Discord: https://discord.com/invite/xZjKRaNp8b

Fit interpretable models. Explain blackbox machine learning.

The iRONS toolbox provides a set of Python functions implementing typical reservoir modelling task and a set of interactive Jupyter Notebooks that demonstrate key functionalities through practical …

Deep learning operations reinvented (for pytorch, tensorflow, jax and others)

DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.

Trax — Deep Learning with Clear Code and Speed

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more