This repository represents an Auto-Encoder which can Encode and Decode itself and give the output at the output layer
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Updated
May 27, 2023 - Jupyter Notebook
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.
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
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.
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.
University of Central Missouri: Spring 2024: CS5720: Neural Network Deep Learning: In Class Programming Assignments
Recommender System in python using autoencoders as part of Data Mining project
DATA: 606 | Capstone Project
variational autoencoder trained on cifar-10 dataset for generative image modelling
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