hyperparameter-tuning

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

The AI Compute Platform for frontier teams. SkyPilot turns fragmented AI compute into one AI supercomputer, so frontier AI teams build custom intelligence faster.

Automated Machine Learning with scikit-learn

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence 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.

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

Automated Machine Learning on Kubernetes

Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

🔥 An autonomous AI agent that runs your deep learning experiments 24/7 while you sleep. Zero-cost monitoring, Leader-Worker architecture, constant-size memory.

SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization

HyperView is a terminal-first TradingView strategy lab for downloading market data, backtesting Python strategies with Pine-like behavior, and optimizing SL/TP parameters.

Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools, with 10x faster training through evolutionary hyperparameter optimization.

EvalML is an AutoML library written in python.

OCTIS: Comparing Topic Models is Simple! A python package to optimize and evaluate topic models (accepted at EACL2021 demo track)

Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning

The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.

Human-explainable AI.