Statistics 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.

A hyperparameter optimization framework

Fast and Accurate ML in 3 Lines of Code

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...

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...

Real-time Web Dashboard for Optuna.

SMAC3: A Versatile Bayesian Optimization Package for 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..)

Notes for Deep Learning Specialization Courses led by Andrew Ng.

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

Fast and Accurate ML in 3 Lines of Code

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

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

Python library for CMA Evolution Strategy.

Real-time Web Dashboard for Optuna.

Code for intrusion detection system (IDS) development using CNN models and transfer learning

Examples for https://github.com/optuna/optuna

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.

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.

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

QSARtuna: QSAR model building with the optuna framework

Code for intrusion detection system (IDS) development using CNN models and transfer learning

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

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

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.