FeedForward Neural Networks Library ifrom scratch implemented using CUDA and vc++, With simple example application for MNIST dataset implementation with 97.82% Accuracy
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Updated
May 31, 2017 - Cuda
FeedForward Neural Networks Library ifrom scratch implemented using CUDA and vc++, With simple example application for MNIST dataset implementation with 97.82% Accuracy
Basic feedforward neural network written from scratch in Python along with a manual explaining how to implement basic neural networks
Implementation of Deep Learning algorithm from scratch
Neural Network with VHDL and matlab
This notebook goes through how to build a neural network using only numpy. The network classifies tumours, identifying if they are malignant or benign. This notebook uses the Breast Cancer Wisconsin dataset.
NeuroJacobian - automatic learning of Jacobian mappings
Neural Network algorithms, concepts and application developed from scratch in python using just numpy, scipy and matplotlib libraries.
A library of neural network implementations written using just Python and NumPy, as a resource for learning.
Implementations of Linear & Logistic Regression, Neural Networks from scratch.
A self coded ANN which can be trained on any data for classification or logistic regression.
implementation of neural network from scratch using javascript
Basic neural network implementation for MNIST dataset. (Numpy, PyTorch)
Keras-style machine learning framework for Java
Neural Network Prototyping library with reactive interface and export code features
PyTorch implementation of Neural Style Transfer
PyTorch seq2seq implementation. Includes pretrained models for jokes<>punchlines and english<>french.
ML Algorithms coded from scratch ( Decision Tree, kNN, Gaussian/Multinomial Naive Bayes )
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