Artificial Neural Networks Python Packages

abrain

ES-HyperNEAT Python implementation with C++ computations for NeuroEvolution, Reinforcement Learning and VfMRI

ebtorch

🤓🔥 Collection of PyTorch additions, extensions, utilities, uses and abuses

imageai

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

keras-models

reusable & predefined models built via Keras, which could be easily integrated into your project.

pytorch-focalloss

PyTorch implementation of binary and multi-class focal loss functions

xtreme-vision

A High Level Python Library to empower students, developers to build applications and systems enabled with computer vision capabilities.

gpt2lm

A implimentation of GPT2 varient.

ejtradermt

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

quickllm

QuickLLM: Fast and Easy Fine-tuning for Popular Language Models

ai-talks

AI Talks - ChatGPT Assistant via Streamlit

neural-network

A Neural Network framework for building and deploying Multi-layer Perceptron models.

modelhub-ai

A collection of deep learning models with a unified API.

densenet-armhzjz

I did my own DenseNet implementation in python.

rctorch

a PyTorch based Reservoir Computing package with Automatic Hyper-Parameter Tuning

unpackai

UnpackAI, the library

msapy

Multi-perturbation Shapley value Analysis (MSA)

flexible-neural-network

A simple and flexible python library that allows you to build custom Neural Networks where you can easily tweak parameters to change how your network behaves

pymilo

PyMilo: Python for ML I/O

lowmind

Ultra-lightweight deep learning framework for Raspberry Pi and embedded systems

torchassistant

A deep learning framework and automation tool built on top of PyTorch

brain-ai

BRAIN - a tool to Build projects and manage Resources for AI Newbies

simpletorch

This repo aims to train neural networks with pytorch. The data are normalized insede the class. The validation is performed automatically. The output model gets the unscaled data and returns the output unscaled (The scaling is performed inside). This way the user do not interact the scaling,; however the user can select to not use the default scaling and scale the data before the training

flashmha

An simple pytorch implementation of Flash MultiHead Attention

supercluster

a novel object-oriented approach to the artificial neural networks inspired by synaptic plasticity between biological neurons