1173 Open source projects that are alternatives of or similar to Color Accessibility Neural Network Deeplearnjs

Log Anomaly Detection - Machine learning to detect abnormal events logs

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

Japanese Riichi Mahjong AI agent. (Feel free to extend this agent or develop your own agent)

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Vector AI — A platform for building vector based applications. Encode, query and analyse data using vectors.

An automatic ML model optimization tool.

Tools for PyTorch

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Theano Implementation of DMN+ (Improved Dynamic Memory Networks) from the paper by Xiong, Merity, & Socher at MetaMind, http://arxiv.org/abs/1603.01417 (Dynamic Memory Networks for Visual and Textual Question Answering)

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Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

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 curated list of GAN & Deepfake papers and repositories.

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A classified list of meta learning papers based on realm.

Hummingbird compiles trained ML models into tensor computation for faster inference.

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Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction: Implementation & Demo

Latex code for making neural networks diagrams

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Deep Object Tracking Implementation in Tensorflow for 'Action-Decision Networks for Visual Tracking with Deep Reinforcement Learning(CVPR 2017)'

Keras + Gaussian Processes: Learning scalable deep and recurrent kernels.

Deep Learning based Automatic Speech Recognition with attention for the Nvidia Jetson.

Detect the programming language of a source code

Face identification with CNN + TPE using Keras

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

Binary and Categorical Focal loss implementation in Keras.

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

Implementation of various self-attention mechanisms focused on computer vision. Ongoing repository.

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

Machine Learning Model for Sport Predictions (Football, Basketball, Baseball, Hockey, Soccer & Tennis)

Scalable Implementation of Deep CFR and Single Deep CFR

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

Understanding emotions from audio files using neural networks and multiple datasets.

Using temporal convolution to detect Audio Deepfakes

Tutorial demonstrating how to create a semantic segmentation (pixel-level classification) model to predict land cover from aerial imagery. This model can be used to identify newly developed or flooded land. Uses ground-truth labels and processed NAIP imagery provided by the Chesapeake Conservancy.

A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and code

Toolbox for converting analog to spiking neural networks (ANN to SNN), and running them in a spiking neuron simulator.

This is a comprehensive ML techniques with python: Define the Problem- Specify Inputs & Outputs- Data Collection- Exploratory data analysis -Data Preprocessing- Model Design- Training- Evaluation

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Various ML/DL Resources organised at a single place.

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

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A cleaner way to build neural networks for PyTorch.

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