Matlab/Octave toolbox for deep learning. Includes Deep Belief Nets, Stacked Autoencoders, Convolutional Neural Nets, Convolutional Autoencoders and vanilla Neural Nets. Each method has examples to get you started.

Deprecation notice. This toolbox is outdated and no longer maintained. There are much better tools available for deep learning than this toolbox, e.g. Theano, torch or tensorflow I would suggest you use one of the tools mention
Category: Python / Deep Learning
Watchers: 472
Star: 3.7k
Fork: 2.3k
Last update: Jan 17, 2022

Related Repos

BaguaSys Bagua is a deep learning training acceleration framework for PyTorch developed by AI [email protected] Technology and DS3 [email protected] ZĆ¼rich. Bagua curren

DEAP DEAP DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data stru

jpmml PySpark2PMML Python library for converting Apache Spark ML pipelines to PMML. Features This package provides Python wrapper classes and functions for

jpmml Sparklyr2PMML R library for converting Apache Spark ML pipelines to PMML. Features This package provides R wrapper classes and functions for the JPMML

h2oai H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

ml31415 numpy-groupies This package consists of a small library of optimised tools for doing things that can roughly be considered "group-indexing operations"

vaexio What is Vaex? Vaex is a high performance Python library for lazy Out-of-Core DataFrames (similar to Pandas), to visualize and explore big tabular data

awslabs Deequ - Unit Tests for Data Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large da

hendrycks Outlier Exposure This repository contains the essential code for the paper Deep Anomaly Detection with Outlier Exposure (ICLR 2019). Requires Python 3

yzhao062 SUOD: Accelerating Large-scare Unsupervised Heterogeneous Outlier Detection Deployment & Documentation & Stats Build Status & Coverage & Maintainabili

tensorflow TensorFlow Data Validation TensorFlow Data Validation (TFDV) is a library for exploring and validating machine learning data. It is designed to be hig

ClimbsRocks auto_ml Automated machine learning for production and analytics Installation pip install auto_ml Getting started from auto_ml import Predictor from au

rsteca sklearn-deap Use evolutionary algorithms instead of gridsearch in scikit-learn. This allows you to reduce the time required to find the best parameter

mattcunningham Naive Bayesian Classifier in APL Ā© 2015-2016 Matthew Cunningham About This is a simple naive bayesian classifier to gain independent probabilistic ass

SeniorSA hybrid-rs-trainner Treine suas engines de recomendaĆ§Ć£o with zero code! :) SumĆ”rio Sistemas de RecomendaĆ§Ć£o Collaborative Filtering Content-Based Filte