Notebooks about Bayesian methods for machine learning

A set of notebooks related to convex optimization, variational inference and numerical methods for signal processing, machine learning, deep learning, graph analysis, bayesian programming, statistics or astronomy.

TensorFlow implementations of several deep learning models (e.g. variational autoencoder, RNN, ...)

Simple Experiments mainly on Machine Learning

Generating images using Variational autoencoders

This repository contains notebooks showcasing various generative models, including DCGAN and VAE for anime face generation, an Autoencoder for converting photos to sketches, a captioning model using an attention mechanism for an image caption generator, and more.

Some coding stuff from various machine learning books

Computer vision notebooks

Implementation notebooks and scripts of Artistic CNN Models and Generative Models like GANs, VAEs, GMMs, Boltzmann Machine etc. in TensorFlow, and Python. This repo aims to understand and make amazing things out of Neural Network layers.

A sparse collection of Machine Learning materials: code, examples, scripts, notebooks etc.

This repository contains my personal notes and Jupyter notebooks on Deep Learning Specialization course at the university Haute-Alsace.

Concepts of Bayesian Statistics, Bayesian inference, computational techniques and knowledge about the different types of models as well as model selection procedures.

A collection of presentations and notebooks on machine learning for automated experiments

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

The repository has scripts and notebooks to train generative models. We specifically aim to train histo-pathology images which are protected under HIPAA law, to make a robust dataset for future pathology computer vision endeavors.