All Algorithms implemented in Python

Deep Learning for humans

AiLearning：数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

Never use print for debugging again

Machine learning, in numpy

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

A Python implementation of global optimization with gaussian processes.

Distributed Asynchronous Hyperparameter Optimization in Python

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space

Scalable and user friendly neural 🧠 forecasting algorithms.

PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)

A function decorator, that rewrites the bytecode, to enable goto in Python

MetPy is a collection of tools in Python for reading, visualizing and performing calculations with weather data.

Automated Deep Learning without ANY human intervention. 1'st Solution for AutoDL challenge@NeurIPS.

ML models and internal tensors 3D visualizer

🎨 A succinct matplotlib wrapper for making beautiful, publication-quality graphics

Kriging Toolkit for Python

OpenSTL: A Comprehensive Benchmark of Spatio-Temporal Predictive Learning

pytorch implemention of trajGRU.

GSTools - A geostatistical toolbox: random fields, variogram estimation, covariance models, kriging and much more

The Python-ARM Radar Toolkit. A data model driven interactive toolkit for working with weather radar data.

Basic data mining model, including feature importance display

Python framework for short-term ensemble prediction systems.

Source code of paper "[NIPS2017] Deep Learning for Precipitation Nowcasting: A Benchmark and A New Model"

A collection of diagnostic and interpolation routines for use with output from the Weather Research and Forecasting (WRF-ARW) Model.

Decode CINRAD (China New Generation Weather Radar) data and visualize.