Implementation of Artificial Neural Networks using NumPy

有空就写点，没空就空着。

A numpy based CNN implementation for classifying images

Building a HTTP-accessed convolutional neural network model using TensorFlow NN (tf.nn), CIFAR10 dataset, Python and Flask.

Semantic Segmentation using Fully Convolutional Neural Network.

ML Prediction of Bible Topics and Passages (Python / React), 2019

Content from the University of British Columbia's Master of Data Science course DSCI 572.

This repository is MLP implementation of classifier on MNIST dataset with PyTorch

neural network and deep learning course projects to work and design on different problems such as classification, regression, optimisation and much more

Landcover classification using the fusion of HSI and LiDAR data.

Tracking S&P 500 index with deep learning model

Nebula: Deep Neural Network Benchmarks in C++

MLP implementation in Python with PyTorch for the MNIST-fashion dataset (90+ on test)

Time series prediction using deep learning

Age estimation with PyTorch

Different kinds of deep neural networks (DNNs) implemented from scratch using Python and NumPy, with a TensorFlow-like object-oriented API.

Linear Regression, Logistic Regression, Fully Connected Neural Network, Recurrent Neural Network, Convolution Neural Network

implementation of neural network from scratch only using numpy (Conv, Fc, Maxpool, optimizers and activation functions)

simple virus DNA classification

Using deep learning and transfer learning techniques to differentiate plain roads and those with potholes using three different classifiers to obtain the best accuracy with the same convolutional base