a simple application of neural network of AI
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Updated
Mar 25, 2017 - JavaScript
a simple application of neural network of AI
Detailed implementation of various machine learning algorithms from scratch using python language.
fast.ai Courses for deep learning beginners
Project for Intro to AI @ UW - Madison Fall 2019
Machine learning experiments in Julia
Training a simple AI using the policy-gradient approach to Reinforcement Learning.
A solution to the 18th_MathModeling Contest
Built a 2-layer, feed-forward neural network and trained it using the back-propagation algorithm to solve a multi-class classification problem for recognizing images of handwritten digits.
Custom Neural Network
Neural_Networks_From_Scratch
This is a software application to detect network intrusion by monitoring a network or system for malicious activity and predicts whether it is Normal or Abnormal(attacked with intrusion classes like DOS/PROBE/R2L/U2R).
Machine Learning Lab JNTUHUCESTH R-21
This project implements the backpropagation algorithm and compares it with pytorch's implementation.
A basic back propagation neural net written in Processing.
Second assignment of Neural and Evolutionary Computation (NEC) at URV
Neural_Network for handwritten numbers detection in Octave (free Matlab)
Encog is a NodeJs ES6 framework based on the Encog Machine Learning Framework by Jeff Heaton.
Implemented gradient descent algorithm and its variants from scratch and visualized their results by training models, for comparison and learning purposes
Code examples of neural networks (learning)
Classification of data using neural networks — with back propagation (multilayer perceptron) and with counter propagation
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