Reduce multiple PyTorch TensorBoard runs to new event (or CSV) files.

PyTorch implementation of (Hinton) Knowledge Distillation and a base class for simple implementation of other distillation methods.

U-Net for biomedical image segmentation

Using tensorboardX (tensorboard for pytorch) e.g. ploting more than one graph in the same chat etc.

This repo helps to track model Weights, Biases and Gradients during training with loss tracking and gives detailed insight for Classification-Model Evaluation

Data visualization using Matplotlib, pandas, seaborn and tensorboard

Comprehensive image classification for training multilayer perceptron (MLP), LeNet, LeNet5, conv2, conv4, conv6, VGG11, VGG13, VGG16, VGG19 with batch normalization, ResNet18, ResNet34, ResNet50, MobilNetV2 on MNIST, CIFAR10, CIFAR100, and ImageNet1K.

This project uses Deep Reinforcement Learning to solve the Lunar Lander environment of the OpenAI-Gym

A Wrapper class for the Tensorflow's Tensorboard.

Crack detection and Crack Length estimation using Deep Neural Networks. Reference: Deep Learning-Based Crack Damage Detection Using Convolutional Neural Networks (Young-Jin Cha & Wooram Choi)

Crack detection and segmentation using a Mask RCNN model from detectron2 library

Dissertation completed for the award of MSci in Computer Science. This dissertation is about automated breast cancer detection in low-resolution whole-slide pathology images using a deep convolutional neural network pipeline.

This is a Pytorch package that can be used directly with PyTorch and Tensorboard to simplify the implementation process.

Simple Feed-Forward Neural Network that classifies characters on the mnist dataset.

Practical use of basic tool for machine learning using PyTorch lib

DCGAN implementation

MLP classifier on the MNIST dataset implemented in JAX with a GUI for entering hyperparameters, and a custom visualization of runs on TensorBoard.

Yet Another Word2Vec Implementation