MSBoost is a gradient boosting algorithm that improves performance by selecting the best model from multiple parallel-trained models for each layer, excelling in small and noisy datasets.

OpenML AutoML Benchmarking Framework

Python package for dataset imports from UCI ML Repository

An original implementation of gradient boosting from scratch

Lazy Predict help build a lot of basic models without much code and helps understand which models works better without any parameter tuning

A powerful and flexible machine learning platform for drug discovery

rdkit总结与实践

Original implementation of the paper "SMILES Transformer: Pre-trained Molecular Fingerprint for Low Data Drug Discovery" by Shion Honda et al.

Acceptance rates for the major AI conferences

Example code from the book "Deep Learning for the Life Sciences"

LaTeX style file for the Journal of Machine Learning Research

Sample code from the Neural Networks from Scratch book.

Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science

Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!

Visualizer for neural network, deep learning and machine learning models

The simplest, fastest repository for training/finetuning medium-sized GPTs.

A LaTeX and WYSIWYG editor with academic search functionality and other helpful tools

Running LambdaMART using XGBoost

TFDS is a collection of datasets ready to use with TensorFlow, Jax, ...

Minimalistic, flat art, and colorful, digital nature wallpapers and an API for randomly selecting them

🎨 A utility for converting images to text art.

Cloud-native Financial Reinforcement Learning

binary releases of VS Code without MS branding/telemetry/licensing

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

Repository to store sample python programs for python learning