ADAS is short for Adaptive Step Size, it's an optimizer that unlike other optimizers that just normalize the derivative, it fine-tunes the step size, truly making step size scheduling obsolete, achieving state-of-the-art training performance

Awesome tutorials, papers, projects and tools for Reservoir Computing techniques like Echo State Networks (ESN).

Huge-scale, high-performance flow cytometry clustering in Julia

Option pricing and Delta hedging performance comparison between Black and Scholes vs Artificial Neural Network

Identify circular trajectories in scRNA-seq data using an autoencoder with sinusoidal activations

Case Studies and Projects in Machine Learning/EDA/DL

Recognize handwritten digits using back-propagation algorithm on MNIST data-set

The implementation of evolvable-substrate HyperNEAT algorithm in GO language. ES-HyperNEAT is an extension of the original HyperNEAT method for evolving large-scale artificial neural networks.

(Machine) Learning to Do More with Less

Innervator: Hardware Acceleration for Neural Networks

A project to filter SQL Injection and XSS attacks using ANN -- in Ruby

Fruit Classifier with ANN

ANN detecting signal from internal variability

Performed data analysis with tensorflow and keras.

A Machine Learning library for Neural Networks fully written in python. It supports multiple layers of neurons and offers a variety of activation functions, optimization algorithms, and utility functions.

Breast cancer prediction🎗️using logistic regression, random forest and artificial neural network

Implementation of algorithms for soft computing

ANN model which identifies why a customer is churning from a bank

Educational pure python neural network implementation with differential evolution (DE) based network weight optimization procedure.