1301 Open source projects that are alternatives of or similar to Awesome Deep Learning For Chinese

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Lets Learn AI

The Cutest Deep Learning Framework which is also a wonderful Declarative Language

Deep Learning Projects that Build Themselves

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

A tutorial for Speech Enhancement researchers and practitioners. The purpose of this repo is to organize the world’s resources for speech enhancement and make them universally accessible and useful.

An open source library for deep learning end-to-end dialog systems and chatbots.

📎 Summaries of papers on deep learning

A complete daily plan for studying to become a machine learning engineer.

Notes, examples, and Python demos for the textbook "Machine Learning Refined" (published by Cambridge University Press).

PHP-ML - Machine Learning library for PHP

Traffic Sign Detection. Code for the paper entitled "Evaluation of deep neural networks for traffic sign detection systems".

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

Learning to Cluster. A deep clustering strategy.

A Python toolkit for Reservoir Computing and Echo State Network experimentation based on pyTorch. EchoTorch is the only Python module available to easily create Deep Reservoir Computing models.

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 …

Top 100 trending deep learning repositories sorted by the number of stars gained on a specific day.

Android TensorFlow Lite Machine Learning Example

A flexible artificial neural network builder to analyse performance, and optimise the best model.

🤖 NanoNeuron is 7 simple JavaScript functions that will give you a feeling of how machines can actually "learn"

Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.

This is the Repository where you can find all the solution of the Problems which you solve on competitive platforms mainly HackerRank and HackerEarth

Human Activity Recognition (HAR) with 1D Convolutional Neural Network in Python and Keras

Time Series Forecast with Bitcoin value, to detect upward/down trends with Machine Learning Algorithms

Top 200 deep learning Github repositories sorted by the number of stars.

A list of the top 10 computer vision papers in 2020 with video demos, articles, code and paper reference.

This is a tutorial for PyTorch Geometric on the YooChoose dataset

A Python package implementing a new machine learning model for text classification with visualization tools for Explainable AI

Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition (https://arxiv.org/pdf/2006.11538.pdf)

Voice Activity Detection based on Deep Learning & TensorFlow

A simple machine learning framework written in Swift 🤖

Applying Machine Learning and AI Algorithms applied to Trading for better performance and low Std.

a delightful machine learning tool that allows you to train, test, and use models without writing code

⏰ AI conference deadline countdowns

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

Alex Castrounis' curated set of resources for artificial intelligence (AI), machine learning, data science, internet of things (IoT), and more.

Gorgonia is a library that helps facilitate machine learning in Go.

🎯 A comprehensive gradient-free optimization framework written in Python

This is an open sourced book on deep learning.

Fabric for Deep Learning (FfDL, pronounced fiddle) is a Deep Learning Platform offering TensorFlow, Caffe, PyTorch etc. as a Service on Kubernetes

deeplearning.ai , By Andrew Ng, All video link

Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks

🍃 Using a Neural Network to improve web accessibility in JavaScript.

A Compositional Object-Based Approach to Learning Physical Dynamics

A collection of computer vision projects for Acute Lymphoblastic Leukemia classification/early detection.

Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning

Caffe2 is a lightweight, modular, and scalable deep learning framework.

Visual Attribute Transfer through Deep Image Analogy in PyTorch!

Daily Dose of Neural Network that Everyone Needs

Python package containing all custom layers used in Neural Networks (Compatible with PyTorch, TensorFlow and MegEngine)

Collection of lectures and lab lectures on machine learning and deep learning. Lab practices in Python and TensorFlow.

Here you can get all the Quantum Machine learning Basics, Algorithms ,Study Materials ,Projects and the descriptions of the projects around the web

TengineKit - Free, Fast, Easy, Real-Time Face Detection & Face Landmarks & Face Attributes & Hand Detection & Hand Landmarks & Body Detection & Body Landmarks & Iris Landmarks & Yolov5 SDK On Mobile.

Season 2 of @twosigma's artificial intelligence programming challenge

💬 Machine Learning Course with Python:

Stochastic Delta Rule implemented in Pytorch on DenseNet

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

Log Anomaly Detection - Machine learning to detect abnormal events logs

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.