My Deep Learning (mdl) is a repository to keep records of the most interesting learnt examples.

This repo is for the demo purpose of Hackntu Data science program.

PyTorch implementation of different types of autoencoders

Comparison between a linear and convolutional autoencoder.

This repository is created as part of Neural Networks and Deep Learning course at my college. This repo contains the implementations of Neural Network and Deep Learning algorithms.

An autoencoder to classify bank transactions as fraudulent or not

A collections of basic autoencoders and Generative models for chemistry

Predict likes , dislikes as well as rating of movies to users

Consists of variety of Autoencoders implementation for various applications such as denoising image, reverse image search, segmantic hair segmentation.

Major Neural Network Architectures - recurrent neural networks, convolutional neural networks, long-short-term-memory, autoencoders, recommender systems, artificial general intelligence

This course will take a look at autoencoders and their applications will help you see how autoencoders are used in dimensionality reduction and denoising. You will implement an artificial neural network and an autoencoder using the Keras framework. By the end of this course, you will be able to implement an autoencoder model using convolutional …

A religion based question answering AI, developed in collaboration for a university course on Design, Thinking and Innovation as part of my bachelor's degree.

Created by Mehmet Zahid Genç

Experiments with different ML techniques using TensorFlow and Sci-kit-learn in Python

This repository if for creating auto-encoders easily. The main focus of the auto-encoders on this page is for genetic and spectral data analysis but likely could be used for any high dimensional data

Deep Learning codes