autoencoders

This repository represents an Auto-Encoder which can Encode and Decode itself and give the output at the output layer

Python autoencoder to remove blur from images

Micro neural network with multi-dimensional layers, multi-shaped data, fully or locally meshing, conv2D, unconv2D, Qlearning, ... for test!

This project is used to detect a credit card fraud detection in an unsupervised manner. An autoencoder- based. an autoencoder with two hidden layer clustering model is build. an autoencoder with two hidden layer and K-means clustering unsupervised machine learning algorithm is used. The data has been taken from Kaggle

Lossy compression autoencoder for a covariance matrix with conditioning. Final project of Computing Methods for Experimental Physics course 2022/2023.

AMS 691.03 Machine Learning in Quant Finance Project

Ad huc solution for anomaly classification of HTTP requests between service and end-user based on limited data / Решение задачи поиска аномальных HTTP запросов (их классификации) к сервису.

Using Deep AutoEncoders (Pytorch) to predict movie ratings

Autoencoder for Feature Extraction

Notes, tutorials, code snippets and templates focused on Autoencoders for Machine Learning

Anomaly detection (also known as outlier analysis) is a data mining step that detects data points, events, and/or observations that differ from the expected behavior of a dataset. A typical data might reveal significant situations, such as a technical fault, or prospective possibilities, such as a shift in consumer behavior.

Text Digit Character Computer Vision using convolutional autoencoder

In this program propose is making an autoencoder with Fully Connected Neural Networks and making a classifier to class encoded MNIST images

This is my academic thesis work (individual). Submitted in partial fulfilment of the requirements for Degree of Bachelor of Science in Computer Science & Engineering

Coloring black and white images using Keras

Using deep learning to predict whether students can correctly answer diagnostic questions