Statistics for topic hyperparameter-optimization

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

A hyperparameter optimization framework

Fast and Accurate ML in 3 Lines of Code

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

QSARtuna: QSAR model building with the optuna framework

Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

A hyperparameter optimization framework

Fast and Accurate ML in 3 Lines of Code

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

QSARtuna: QSAR model building with the optuna framework

Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Fast and Accurate ML in 3 Lines of Code

A hyperparameter optimization framework

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

Parallel Hyperparameter Tuning in Python

Interactive coding assistant for data scientists and machine learning developers, empowered by large language models.

A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.

A convenient way to trigger synchronizations to wandb / Weights & Biases if your compute nodes don't have internet!

Nomadic is an enterprise-grade framework for teams to continuously optimize compound AI systems

Nomadic is an enterprise-grade framework for teams to continuously optimize compound AI systems

A Library for Conformal Hyperparameter Tuning

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

A hyperparameter optimization framework

The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.

Fast and Accurate ML in 3 Lines of Code

Nomadic is an enterprise-grade framework for teams to continuously optimize compound AI systems

QSARtuna: QSAR model building with the optuna framework

Interactive coding assistant for data scientists and machine learning developers, empowered by large language models.

Neural Pipeline Search (NePS): Helps deep learning experts find the best neural pipeline.

A PyTorch implementation of Latent Factor Analysis via Dynamical Systems (LFADS) and AutoLFADS.