automatic-machine-learning
There are 29 repositories under automatic-machine-learning topic.
sb-ai-lab/LightAutoML
Fast and customizable framework for automatic ML model creation (AutoML)
PKU-DAIR/open-box
Towards Generalized and Efficient Blackbox Optimization System/Package (KDD 2021 & JMLR 2024)
Alex-Lekov/AutoML_Alex
State-of-the art Automated Machine Learning python library for Tabular Data
Vatshayan/Face-recognition-Attendance-System-Project
Final Year Btech Face recognition Attendance System Project with code and Documents. Video Implementation with explanation too. Base IEEE paper Implementation
negrinho/deep_architect_legacy
DeepArchitect: Automatically Designing and Training Deep Architectures
negrinho/deep_architect
A general, modular, and programmable architecture search framework
batermj/data_sciences_campaign
【数据科学家系列课程】
thomas-young-2013/open-box
Generalized and Efficient Blackbox Optimization System.
r-tensorflow/autokeras
Package: R Interface to AutoKeras
spsanderson/tidyAML
Auto ML for the tidyverse
KhiopsML/khiops
Khiops is an AutoML suite for supervised and unsupervised learning
haghish/mlim
mlim: single and multiple imputation with automated machine learning
georgian-io-archive/foreshadow
An automatic machine learning system
mljar/automl_comparison
Comparison of automatic machine learning libraries
KhiopsML/khiops-python
The Python library of the Khiops AutoML suite
tgbnhy/fast-kmeans
This repo holds the code, dataset, and running scripts for fast k-means evaluation
sergio94al/Automatic_design_of_quantum_feature_maps_Genetic_Auto-Generation
Registered Software. Official code of the published article "Automatic design of quantum feature maps". This quantum machine learning technique allows to auto-generate quantum-inspired classifiers by using multiobjetive genetic algorithms for tabular data.
mlpapers/automl
Awesome papers on AutoML (Automatic Machine Learning)
phbillet/EzStacking
EzStacking: From data to Kubernetes thru Scikit-Learn, FastAPI and Docker in a few clicks and command lines!
alankrantas/colab-python-cookbooks
Experiments of AutoML/data science packages and solving Kaggle competition in Google Colaboratory or DevContainer/Codespace
PedroSeber/SmartProcessAnalytics
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.
light-weaver/ModelSelector
Surrogarte modelling technique selector
AlbertoCampini/AAUT
Apprendimento automatico
Danielto1404/master-courses
A collection of courses at Master program at Deep Learning department in ITMO University
mghasemi/sksurrogate
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).
arjunan-k/Auto_ML_PyCaret
Automate machine learning EDA and model building using Pandas Profiling & PyCaret.
sergio94al/AutoQML-Quantum-Inspired-Kernels-by-Using-Genetic-Algorithms-for-Grayscale-images
This quantum machine learning technique allows to auto-generate quantum-inspired classifiers by using multiobjetive genetic algorithms for grayscale images, optimizing both quantum circuits and dimensionality reduction method.
MuhamedHekal/images-classification-Scones-Unlimited
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 optimize their operations.