Simple and reliable optimization with local, global, population-based and sequential techniques in numerical discrete search spaces.

Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.

Fast and Accurate ML in 3 Lines of Code

🔥 A tool for visualizing and tracking your machine learning experiments. This repo contains the CLI and Python API.

Implementation of a comparative analysis to find the best ML model for classifying dry eye disease from healthy controls using metabolomics datasets.

A hyperparameter optimization framework

Real-time Web Dashboard for Optuna.

Minerva is a framework for training machine learning models for researchers.

Tutorials for the optimization techniques used in Gradient-Free-Optimizers and Hyperactive.

This is a remake of my Capstone Project on Image Classification using Scikit-learn and TensorFlow. I initially completed this project as a part of my Data Science diploma studies at Brainstation in June 2023.

Machine Learning Toolbox 2

Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.

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

Python library for CMA Evolution Strategy.

Automated modeling and machine learning framework FEDOT

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

Deterministic algorithms for objective Bayesian inference and hyperparameter optimization

RNN-LSTM: From Applications to Modeling Techniques and Beyond - Systematic Review