aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

Learn OpenCV : C++ and Python Examples

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

Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…

This repository contains the source code for the paper First Order Motion Model for Image Animation

The "Python Machine Learning (1st edition)" book code repository and info resource

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K…

Repository of teaching materials, code, and data for my data analysis and machine learning projects.

From the basics to slightly more interesting applications of Tensorflow

A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks

Repo for the Deep Learning Nanodegree Foundations program.

Lectures on scientific computing with python, as IPython notebooks.

Машинное обучение на ФКН ВШЭ

Official Implementation for "Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation" (CVPR 2021) presenting the pixel2style2pixel (pSp) framework

TensorFlow Tutorials

A python tutorial on bayesian modeling techniques (PyMC3)

I took Andrew Ng's Machine Learning course on Coursera and did the homework assigments... but, on my own in python because I love jupyter notebooks!

Practical tutorials and labs for TensorFlow used by Nvidia, FFN, CNN, RNN, Kaggle, AE

Notebooks about Bayesian methods for machine learning

DL course co-developed by YSDA, HSE and Skoltech

Slides and Jupyter notebooks for the Deep Learning lectures at Master Year 2 Data Science from Institut Polytechnique de Paris

Generative adversarial networks integrating modules from FUNIT and SPADE for face-swapping.

FSGAN - Official PyTorch Implementation

Evaluation of the CNN design choices performance on ImageNet-2012.

Deep learning for audio processing

Code companion to the O'Reilly "Fundamentals of Deep Learning" book

Enabling journalists, citizen scientists, humanitarian workers and others to detect “patterns of interest” in satellite imagery.

My solutions to Kevin Murphy Machine Learning Book