933 Open source projects that are alternatives of or similar to Ensemble Pytorch

A unified ensemble framework for PyTorch to improve the performance and robustness of your deep learning model.

Deep Learning over PyTorch

Amacımız Türkçe NLP literatüründeki birçok farklı sorunu bir arada çözebilen, eşsiz yaklaşımlar öne süren ve literatürdeki çalışmaların eksiklerini gideren open source bir yazım destekleyicisi/denetleyicisi oluşturmak. Kullanıcıların yazdıkları metinlerdeki yazım yanlışlarını derin öğrenme yaklaşımıyla çözüp aynı zamanda metinlerde anlamsal analizi de gerçekleştirerek bu bağlamda ortaya çıkan yanlışları da fark edip düzeltebilmek.

Computer code collated for use with Artificial Intelligence Engines book by JV Stone

PaddlePaddle End-to-End Development Toolkit（『飞桨』深度学习全流程开发工具）

A Keras CTC implementation of Baidu's DeepSpeech for model experimentation

A minimalist deep learning library in Javascript using WebGL + asm.js. Run convolutional neural network in your browser.

An introductory series to Reinforcement Learning (RL) with comprehensive step-by-step tutorials.

Lab Materials for MIT 6.S191: Introduction to Deep Learning

Deep Kernel Learning. Gaussian Process Regression where the input is a neural network mapping of x that maximizes the marginal likelihood

PyTorch Tutorial for Deep Learning Researchers

머신러닝 입문자 혹은 스터디를 준비하시는 분들에게 도움이 되고자 만든 repository입니다. (This repository is intented for helping whom are interested in machine learning study)

Ergonomic machine learning for everyone.

All DeepLearning4j projects go here.

machine learning and deep learning tutorials, articles and other resources

DeepFaceLab is the leading software for creating deepfakes.

MIT Deep Learning Book in PDF format (complete and parts) by Ian Goodfellow, Yoshua Bengio and Aaron Courville

The SpeechBrain project aims to build a novel speech toolkit fully based on PyTorch. With SpeechBrain users can easily create speech processing systems, ranging from speech recognition (both HMM/DNN and end-to-end), speaker recognition, speech enhancement, speech separation, multi-microphone speech processing, and many others.

pytorch 包教不包会

由淺入深的深度學習資源 Collection of deep learning materials for everyone

Implementation of Quickdraw - an online game developed by Google

This repositary is a combination of different resources lying scattered all over the internet. The reason for making such an repositary is to combine all the valuable resources in a sequential manner, so that it helps every beginners who are in a search of free and structured learning resource for Data Science. For Constant Updates Follow me in …

Tutorials, assignments, and competitions for MIT Deep Learning related courses.

Getting started with AllenNLP and PyTorch by training a tweet classifier

Code and data accompanying Natural Language Processing with PyTorch published by O'Reilly Media https://nlproc.info

PyTorch 101 series covering everything from the basic building blocks all the way to building custom architectures.

Deepfakes Software For All

List of articles related to deep learning applied to music

Bidirectional Attention Flow for Machine Comprehension implemented in Keras 2

SSD: Single Shot MultiBox Detector pytorch implementation focusing on simplicity

FastText for Node.js

A High-Quality PyTorch Implementation of "Globally and Locally Consistent Image Completion".

Anomaly detection tutorial on univariate time series with an auto-encoder

Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood.

👋 ML/DL学习笔记（基础+论文）

Pretrain and finetune ELECTRA with fastai and huggingface. (Results of the paper replicated !)

Tel-Aviv Deep Learning Boot-camp: 12 Applied Deep Learning Labs

🐰 Python lib for remo - the app for annotations and images management in Computer Vision

A P300 online spelling mechanism for Emotiv headsets. It's completely written in Node.js, and the GUI is based on Electron and Vue.

My journey to learn and grow in the domain of Machine Learning and Artificial Intelligence by performing the #100DaysofMLCode Challenge.

Python Adaptive Signal Processing

PyTorch (and PyTorch Lightning) implementation of Neural Style Transfer, Pix2Pix, CycleGAN, and Deep Dream!

🛠 All-in-one web-based IDE specialized for machine learning and data science.

深度学习入门开源书，基于TensorFlow 2.0案例实战。Open source Deep Learning book, based on TensorFlow 2.0 framework.

Pytorch implementation of Block Neural Autoregressive Flow

Deep neural network to extract intelligent information from invoice documents.

AI on Hadoop

Code for reproducing Flow ++ experiments

A powerful and intuitive WYSIWYG interface that allows anyone to create Machine Learning models!

OpenBot leverages smartphones as brains for low-cost robots. We have designed a small electric vehicle that costs about $50 and serves as a robot body. Our software stack for Android smartphones supports advanced robotics workloads such as person following and real-time autonomous navigation.

NCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.

An easy-to-use interface for measuring uncertainty and robustness.

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

Unity Machine Learning Agents Toolkit

Important paper implementations for Question Answering using PyTorch

CryptoNets is a demonstration of the use of Neural-Networks over data encrypted with Homomorphic Encryption. Homomorphic Encryptions allow performing operations such as addition and multiplication over data while it is encrypted. Therefore, it allows keeping data private while outsourcing computation (see here and here for more about Homomorphic Encryptions and its applications). This project demonstrates the use of Homomorphic Encryption for outsourcing neural-network predictions. The scenario in mind is a provider that would like to provide Prediction as a Service (PaaS) but the data for which predictions are needed may be private. This may be the case in fields such as health or finance. By using CryptoNets, the user of the service can encrypt their data using Homomorphic Encryption and send only the encrypted message to the service provider. Since Homomorphic Encryptions allow the provider to operate on the data while it is encrypted, the provider can make predictions using a pre-trained Neural-Network while the data remains encrypted throughout the process and finaly send the prediction to the user who can decrypt the results. During the process the service provider does not learn anything about the data that was used, the prediction that was made or any intermediate result since everything is encrypted throughout the process. This project uses the Simple Encrypted Arithmetic Library SEAL version 3.2.1 implementation of Homomorphic Encryption developed in Microsoft Research.

Probabilistic time series modeling in Python

This repository contains the code of LiviaNET, a 3D fully convolutional neural network that was employed in our work: "3D fully convolutional networks for subcortical segmentation in MRI: A large-scale study"

Various CNN models for CIFAR10 with Chainer