Top 106 artificial-neural-networks open source projects

Evaluate three types of task shifting with popular continual learning algorithms.

Udemy Derin Öğrenmeye Giriş Kursunun Uygulamaları ve Daha Fazlası

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.

A Knowledge Base for the FB Group Artificial Intelligence and Deep Learning (AIDL)

🚀 FREE AI Resources - 🎓 Courses, 👷 Jobs, 📝 Blogs, 🔬 AI Research, and many more - for everyone!

Always sparse. Never dense. But never say never. A repository for the Adaptive Sparse Connectivity concept and its algorithmic instantiation, i.e. Sparse Evolutionary Training, to boost Deep Learning scalability on various aspects (e.g. memory and computational time efficiency, representation and generalization power).

👨🏽‍🏫You can learn about what data science is and why it's important in today's modern world. Are you interested in data science?🔋

An Architecture Combining Convolutional Neural Network (CNN) and Linear Support Vector Machine (SVM) for Image Classification

TensorFlow C API Class Wrapper in Server Side Swift.

Code for Java Deep Learning Cookbook

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

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

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

A Neural Networking library based on NumPy only

The light deep learning framework for study and for fun. Join us!

Artificial Neural Networks for Scala

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

A brain-inspired version of generative replay for continual learning with deep neural networks (e.g., class-incremental learning on CIFAR-100; PyTorch code).

Rocket powered machine learning. Create, compare, adapt, improve - artificial intelligence at the speed of thought.

CAI NEURAL API - Pascal based neural network API optimized for AVX, AVX2 and AVX512 instruction sets plus OpenCL capable devices including AMD, Intel and NVIDIA.

Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!

Towards Building an Intelligent Anti-Malware System: A Deep Learning Approach using Support Vector Machine for Malware Classification

This is a collection of some of the important machine learning algorithms which are implemented with out using any libraries. Libraries such as numpy and pandas are used to improve computational complexity of algorithms

[ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection

Use unsupervised and supervised learning to predict stocks

Handwritten digits, a bit like the MNIST dataset.

A 2D Unity simulation in which cars learn to navigate themselves through different courses. The cars are steered by a feedforward neural network. The weights of the network are trained using a modified genetic algorithm.

simple neural network library in ANSI C

Collection of various implementations and Codes in Machine Learning, Deep Learning and Computer Vision ✨💥

MIVisionX toolkit is a comprehensive computer vision and machine intelligence libraries, utilities and applications bundled into a single toolkit.

Yet another neural network library

Courses, Articles and many more which can help beginners or professionals.

Unsupervised ML algorithm for predictive modeling and time-series analysis

An Interactive Approach to Understanding Deep Learning with Keras

A deep learning based gaze estimation framework implemented with PyTorch

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

C# implementation of the various algorithms based on Genetic Algorithm, Genetic Programming and Artificial Neural Networks.

A python library built to empower developers to build applications and systems with self-contained Computer Vision capabilities

NeuPy is a Tensorflow based python library for prototyping and building neural networks

Re-implementation of TensorFlow in pure python, with an emphasis on code understandability

deeplearning.ai , By Andrew Ng, All video link

Fast Deep Learning Library (DLL) for C++ (ANNs, CNNs, RBMs, DBNs...)

PyTorch implementation of various methods for continual learning (XdG, EWC, online EWC, SI, LwF, GR, GR+distill, RtF, ER, A-GEM, iCaRL).

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

Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)

🤖 A portable, header-only, artificial neural network library written in C99

Curso de Introducción a Machine Learning con Python

This is an open sourced book on deep learning.

PyTorch - Python + Nim

NiuTensor is an open-source toolkit developed by a joint team from NLP Lab. at Northeastern University and the NiuTrans Team. It provides tensor utilities to create and train neural networks.

The simplest form of an artificial neural network explained and demonstrated.

Curated Tensorflow code resources to help you get started with Deep Learning.

Code for training and test machine learning classifiers on MIT-BIH Arrhyhtmia database

A curated list of awesome awesomeness about artificial intelligence

Learning to Cluster. A deep clustering strategy.

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

An easy, flexible, and accurate plate recognition project for Chinese licenses in unconstrained situations.

Go implementation of Leabra algorithm for biologically-based models of cognition, based on emergent framework (with Python interface)

Useful Toolbox for Anomaly Detection

EmbeddedML was created to be an alternative to the limited options available for Artificial Neural Networks in C. It is designed to be efficient without sacrificing ease of use. It is meant to support students as well as industry experts as it is built to be expandable and straightforward to manipulate.