172 Open source projects that are alternatives of or similar to bbai

A simple, extensible library for developing AutoML systems

[UNMAINTAINED] Automated machine learning for analytics & production

In this repository you can find many different, small, projects which demonstrate regression techniques using python programming language

Toolbox for Bayesian Optimization and Model-Based Optimization in R

Efficient Hyperparameter Optimization of Deep Learning Algorithms Using Deterministic RBF Surrogates

OptKeras: wrapper around Keras and Optuna for hyperparameter optimization

Milano is a tool for automating hyper-parameters search for your models on a backend of your choice.

Scalable, structured, dynamically-scheduled hyperparameter optimization.

A fully decentralized hyperparameter optimization framework

Python code for bayesian optimization using Gaussian processes

A hyperparameter optimization and data collection toolbox for convenient and fast prototyping of machine-learning models.

Determined: Deep Learning Training Platform

A library for doing Bayesian Optimization using Gaussian Processes (blackbox optimizer) in Go/Golang.

A collection of pre-trained RL agents using Stable Baselines3, training and hyperparameter optimization included.

Parallel Hyperparameter Tuning in Python

mlmodels : Machine Learning and Deep Learning Model ZOO for Pytorch, Tensorflow, Keras, Gluon models...

Best Subset Selection algorithm for Regression, Classification, Count, Survival analysis

State-of-the art Automated Machine Learning python library for Tabular Data

Real-time Web Dashboard for Optuna.

A toolset for black-box hyperparameter optimisation.

A Clojure machine learning library

Hyperparameter Optimization for TensorFlow, Keras and PyTorch

Transformations to contrained variables from ℝⁿ.

Python library for CMA Evolution Strategy.

Library for Semi-Automated Data Science

Asynchronous Distributed Hyperparameter Optimization.

Purely functional genetic algorithms for multi-objective optimisation

Development of the R package 'Luminescence'

Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization

Bayesian spatial analysis

An automatic ML model optimization tool.

R package for fitting joint models to time-to-event data and multivariate longitudinal data

Gradient based hyperparameter optimization & meta-learning package for TensorFlow

Polyaxon Core Client & CLI to streamline MLOps

Time Series Cross-Validation -- an extension for scikit-learn

A scikit-learn compatible implementation of hyperband

DeepArchitect: Automatically Designing and Training Deep Architectures

Utilities for glmnet

Population Based Training (in PyTorch with sqlite3). Status: Unsupported

A General Automated Machine Learning framework to simplify the development of End-to-end AutoML toolkits in specific domains.

Notes for Deep Learning Specialization Courses led by Andrew Ng.

In depth analysis and forecasting of product sales based on the items, stores, transaction and other dependent variables like holidays and oil prices.

Bilevel Optimization Library in Python for Multi-Task and Meta Learning

Separating Normalizing Flows code from Pyro and improving API

DeepHyper: Scalable Asynchronous Neural Architecture and Hyperparameter Search for Deep Neural Networks

a collection of modern sparse (regularized) linear regression algorithms.

A general, modular, and programmable architecture search framework

An open source framework that provides a simple, universal API for building distributed applications. Ray is packaged with RLlib, a scalable reinforcement learning library, and Tune, a scalable hyperparameter tuning library.

An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.

Solutions of practice problems from the Richard McElreath's "Statistical Rethinking" book.

Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.

Bayesian Optimization using GPflow

A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling in Python.

Helpers for regression analyses using `{broom}` & `{easystats}` packages 📈 🔍

A Python library for the state-of-the-art Bayesian optimization algorithms, with the core implemented in C++.

Tools for an Aesara-based PPL.

An introductory statistics course for social scientists, using Stata

Blang's software development kit

Hyperparameter optimization package of the mlr3 ecosystem

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