A complete implementation of neural network with forward and back-propagation in python numpy for fitting a line
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Updated
Feb 22, 2017 - Python
A complete implementation of neural network with forward and back-propagation in python numpy for fitting a line
My solution to the 2nd assignment of UdelaR's Deep Learning course, based on Stanford CS231n.
Implementation of neural networks from scratch using Python
An image classifier that uses the CIFAR-10 data set for training. This is Project-2 of Udacity's Deep Learning Foundations Nanodegree.
Neon code for Splice Junction Gene Sequence training and classification (EI / IE / Neither)
Sentimental analysis on IMDB using tflearn Deep Neural Network
Train a Tic-Tac-Toe and a Connect-4 player using the TD-lambda algorithm
This is an implementation of a fully connected feedforward Neural Network (multi-layer perceptron) from scratch to classify MNIST hand-written digits
A classical XOR neural network using pytorch
MultiLayer Perceptron para identificación de números escritos a mano de 28x28.
Open Source C++ Library for Pseudo-inverse Fully Connected Recurrent Neural Networks (from my PhD)
This repository holds one of my first Deep Learning projects. The project implements an MNIST classifying fully-connected neural network from scratch (in python) using only NumPy for numeric computations. For further information, please see README.
Simple Python implementation of a fully connected neural network
Age estimation with PyTorch
Linear Regression, Logistic Regression, Fully Connected Neural Network, Recurrent Neural Network, Convolution Neural Network
A fully connected neural net implemented by Numpy
This repository is MLP implementation of classifier on MNIST dataset with PyTorch
A project for my Advanced Artificial Intelligence class to apply AI methods to a real-world problem.
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