418 Open source projects that are alternatives of or similar to Neural Cryptography Tensorflow

👷‍♂️ A simple package for extracting useful features from character objects 👷‍♀️

Lacmus is a cross-platform application that helps to find people who are lost in the forest using computer vision and neural networks.

Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras

Notes & exercise solutions of Part I from the book: "Hands-On ML with Scikit-Learn, Keras & TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems" by Aurelien Geron

Pytorch implementation of Block Neural Autoregressive Flow

Ergonomic machine learning for everyone.

machine learning and deep learning tutorials, articles and other resources

🚪✊Knock Knock: Get notified when your training ends with only two additional lines of code

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

Avalanche: a End-to-End Library for Continual Learning.

KitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.

Unity Machine Learning Agents Toolkit

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.

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

A blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.

Julia port of the Python autograd package.

Autodifferentiation package in Rust.

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"

Video Platform for Action Recognition and Object Detection in Pytorch

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

Code repository for Frontiers article 'Generative Adversarial Networks for Image-to-Image Translation on Multi-Contrast MR Images - A Comparison of CycleGAN and UNIT'

Python Adaptive Signal Processing

🟣 Object detection of abstract shapes with neural networks

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.

Frame-Recurrent Video Super-Resolution (official repository)

Machine Learning inference engine for Microcontrollers and Embedded devices

Various CNN models for CIFAR10 with Chainer

Awesome machine learning model compression research papers, tools, and learning material.

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.

List of articles related to deep learning applied to music

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

💥 Fast matrix-multiplication as a self-contained Python library – no system dependencies!

Probabilistic time series modeling in Python

A repository of state-of-the-art deep learning methods in computer vision

Deep Learning for Julia

Improved Residual Networks (https://arxiv.org/pdf/2004.04989.pdf)

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

Spying using Smartwatch and Deep Learning

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

Graph Attention Networks (https://arxiv.org/abs/1710.10903)

EnhanceNet: Single Image Super-Resolution Through Automated Texture Synthesis (official repository)

Just another DL library

A collection of common algorithms and data structures implemented in java, c++, and python.

A single / multi layer / recurrent neural network written in Golang.

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

Concise deep learning for JAX

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

Scalable Implementation of Deep CFR and Single Deep CFR

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

All about attention in neural networks. Soft attention, attention maps, local and global attention and multi-head attention.

Code for reproducing Flow ++ experiments

[NO MAINTENANCE INTENDED] A PyTorch implementation of CapsNet architecture in the NIPS 2017 paper "Dynamic Routing Between Capsules".

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

LATEX: TikZ package for drawing neural networks. Also available on CTAN at http://www.ctan.org/tex-archive/graphics/pgf/contrib/neuralnetwork

Implementation of the paper "Adversarial Attacks on Neural Networks for Graph Data".

Anomaly detection for temporal data using LSTMs

Brain Modeling Toolkit

Introductions to key concepts in quantum machine learning, as well as tutorials and implementations from cutting-edge QML research.

An automatic ML model optimization tool.

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