Comparison of automatic machine learning libraries

DeepArchitect: Automatically Designing and Training Deep Architectures

Surrogarte modelling technique selector

Package: R Interface to AutoKeras

Awesome papers on AutoML (Automatic Machine Learning)

This repo holds the code, dataset, and running scripts for fast k-means evaluation

Final Year Btech Face recognition Attendance System Project with code and Documents. Video Implementation with explanation too. Base IEEE paper Implementation

In this project, I'll be building an image classification model that can automatically detect which kind of vehicle delivery drivers have, in order to route them to the correct loading bay and orders. Assigning delivery professionals who have a bicycle to nearby orders and giving motorcyclists orders that are farther can help Scones Unlimited op…

Automate machine learning EDA and model building using Pandas Profiling & PyCaret.

Generalized and Efficient Blackbox Optimization System.

Apprendimento automatico

A general, modular, and programmable architecture search framework

A collection of courses at Master program at Deep Learning department in ITMO University

SKSurrogate is a suite of tools that implements surrogate optimization for expensive functions based on scikit-learn. The main purpose of SKSurrogate is to facilitate hyperparameter optimization for machine learning models and optimized pipeline design (AutoML).

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

mlim: single and multiple imputation with automated machine learning

An automatic machine learning system

Fast and customizable framework for automatic ML model creation (AutoML)

Smart Process Analytics (SPA) is a software package for automatic machine learning. Given user-input data (and optional user preferences), SPA automatically cross-validates and tests ML and DL models. Model types are selected based on the properties of the data, minimizing the risk of data-specific variance.