Create a neural network through TensorFlow and Keras to build a model which has the ability to assess an organisation's ability to be successful with funding from the Alphabet Soup charity

Python neural network built from scratch. Uses Machine Learning algorithms to correctly classify handwritten numbers into digits.

Neural backpropagation with examples and training (Java)

Predicting Indian stock prices using Stacked LSTM model. Analysing Reliance, Tata Steel, HDFC Bank, Infosys data. Data prep, EDA, hyperparameter tuning.

simple neural network library in ANSI C

Nonprofit foundation Alphabet Soup wants a tool that can help it select the applicants for funding with the best chance of success in their ventures. Using machine learning and neural networks, you’ll use the features in the provided dataset to create a binary classifier that can predict whether applicants will be successful if funded.

Neural Networks scratch

The nonprofit foundation Alphabet Soup wants a tool that can help it select the applicants for funding with the best chance of success in their ventures

Implementation of Artificial Neural Networks using NumPy

NU Bootcamp Module 21

Deep Neural Network Classifier for the Win/Linux/OSX platform based on the GTK# Framework

This repository covers the practical applications of Deep Learning

Looking at the manifold hypothesis in deep learning. Creating a simple spiral dataset allows me to reveal how neural networks follow an optimal packing strategy during their training.

"One Hidden Layer Neural Network" from Scratch

"Deep Neural Network" from Scratch

Using keras specify-compile-fit- predict workflow on this binary classification problem to investigate if i'll get better predictions.

Genann library port to C# (unsafe version), simple neural network library

Compiled, trained, evaluated, and optimized models using Neural Networks and Deep Learning Models.

This code implements neural network from scratch without using any library