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13 search results found

Imageai ⭐ 8,051

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

Awesome Quantum Machine Learning ⭐ 2,206

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

Hyperparameter Optimization Of Machine Learning Algorithms ⭐ 1,025

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

Continual Learning Benchmark ⭐ 158

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

Numpyann ⭐ 95

Implementation of Artificial Neural Networks using NumPy

Quant Finance Resources ⭐ 95

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

A recurrent/memory-based neural network library implemented from scratch in C.

Ejtradermt ⭐ 40

Metatrader 5 API - Trading and history OHLC Dataframe in Nano Seconds

Environment to play around with algorithms and data

A collection of Deep Reinforcement Learning algorithms implemented in tensorflow. Very extensible. High performing DQN implementation.

Wargames ⭐ 22

Two agents shooting at each other, controlled by a neural network optimized with a genetic algorithm.

Gpdotnetv4 ⭐ 20

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

Implementation of machine learning and artificial intelligence algorithms in lua with demo using game bot

Tensorflow_node ⭐ 11

Tensorflow based ROS node for evaluating deep learning algorithms.

The Machine Learning Workshop ⭐ 9

An interactive approach to understanding Machine Learning using scikit-learn

Gpu Cuda Self Organising Maps ⭐ 7

🧠 💡 📈 A project based in High Performance Computing. This project was built using CUDA (Compute Unified Device Architecture), C++ (C Plus Plus), C, CMake and JetBrains CLion. The scenario of the project was a GPU-based implementation of the Self-Organising-Maps (S.O.M.) algorithm for Artificial Neural Networks (A.N.N.), with the support of CUDA (Compute Unified Device Architecture), using its offered parallel optimisations and tunings. The final goal of the project was to test the several GPU

Sign Language Recognition Using Scikit Learn And Cnn ⭐ 7

The project aims at building a machine learning model that will be able to classify the various hand gestures used for fingerspelling in sign language. In this user independent model, classification machine learning algorithms are trained using a set of image data and testing is done. Various machine learning algorithms are applied on the datasets, including Convolutional Neural Network (CNN).

A library for creating Artificial Neural Networks, for use in Machine Learning and Deep Learning algorithms.

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