Trending repositories for topic hyperparameter-optimization
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.
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry throug...
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 Neur...
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
A curated list of automated machine learning papers, articles, tutorials, slides and projects
A curated list of awesome Distributed Deep Learning resources.
Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry throug...
A curated list of awesome Distributed Deep Learning resources.
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
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 Neur...
Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
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 fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
A curated list of automated machine learning papers, articles, tutorials, slides and projects
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
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.
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
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 Neur...
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry throug...
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
A convenient way to trigger synchronizations to wandb / Weights & Biases if your compute nodes don't have internet!
A curated list of automated machine learning papers, articles, tutorials, slides and projects
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
🐟Tunny🐟 is Grasshopper's optimization component using Optuna, an open source hyperparameter auto-optimization framework.
A convenient way to trigger synchronizations to wandb / Weights & Biases if your compute nodes don't have internet!
🐟Tunny🐟 is Grasshopper's optimization component using Optuna, an open source hyperparameter auto-optimization framework.
Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
Code for intrusion detection system (IDS) development using CNN models and transfer learning
Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry throug...
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 Neur...
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
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 curated list of awesome Distributed Deep Learning resources.
A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.
A curated list of automated machine learning papers, articles, tutorials, slides and projects
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 collection of 100+ pre-trained RL agents using Stable Baselines, training and hyperparameter optimization included.
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.
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
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 Neur...
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.
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry throug...
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
A curated list of automated machine learning papers, articles, tutorials, slides and projects
A convenient way to trigger synchronizations to wandb / Weights & Biases if your compute nodes don't have internet!
A convenient way to trigger synchronizations to wandb / Weights & Biases if your compute nodes don't have internet!
🐟Tunny🐟 is Grasshopper's optimization component using Optuna, an open source hyperparameter auto-optimization framework.
Propulate is an asynchronous population-based optimization algorithm and software package for global optimization and hyperparameter search on high-performance computers.
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 PyTorch implementation of Latent Factor Analysis via Dynamical Systems (LFADS) and AutoLFADS.
Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
A training framework for Stable Baselines3 reinforcement learning agents, with hyperparameter optimization and pre-trained agents included.
Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)
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 Neur...
An online learning method used to address concept drift and model drift. Code for the paper entitled "A Lightweight Concept Drift Detection and Adaptation Framework for IoT Data Streams" published in ...
Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry throug...
An Ensemble DL Model Tuned with Genetic Algorithm for Oil Production Forecasting.
Intelligently optimizes technical indicators and optionally selects the least intercorrelated for use in machine learning models
Neural Pipeline Search (NePS): Helps deep learning experts find the best neural pipeline.
Nomadic is an enterprise-grade framework for teams to continuously optimize compound AI systems
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.
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
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 Neur...
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
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.
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
Robyn is an experimental, AI/ML-powered and open sourced Marketing Mix Modeling (MMM) package from Meta Marketing Science. Our mission is to democratise modeling knowledge, inspire the industry throug...
A curated list of automated machine learning papers, articles, tutorials, slides and projects
Streamlining reinforcement learning with RLOps. State-of-the-art RL algorithms and tools.
MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle
Nomadic is an enterprise-grade framework for teams to continuously optimize compound AI systems
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.
A convenient way to trigger synchronizations to wandb / Weights & Biases if your compute nodes don't have internet!
An Ensemble DL Model Tuned with Genetic Algorithm for Oil Production Forecasting.
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
MetaBox: A Benchmark Platform for Meta-Black-Box Optimization with Reinforcement Learning (https://arxiv.org/abs/2310.08252)
Code for intrusion detection system (IDS) development using CNN models and transfer learning
🐟Tunny🐟 is Grasshopper's optimization component using Optuna, an open source hyperparameter auto-optimization framework.
A portfolio optimization tool with scikit-learn interface. Hyperparameters selection and easy plotting of efficient frontiers.
Deterministic algorithms for objective Bayesian inference and hyperparameter optimization
Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)
Propulate is an asynchronous population-based optimization algorithm and software package for global optimization and hyperparameter search on high-performance computers.
Improve prompts for e.g. GPT3 and GPT-J using templates and hyperparameter optimization.