khamv Goto Github PK

blog

blog

cs231n-2017

Completed the CS231n spring 2017 assignments from Stanford university

faceswap-gan

A GAN model built upon deepfakes' autoencoder for face swapping.

hexagdly

Process hexagonally sampled data with PyTorch

kalman-and-bayesian-filters-in-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 filters, and more. All exercises include solutions.

khamv.github.io

Personal Blog

mashinnoye-obucheniye

:books: Специализация «Машинное обучение и анализ данных»

ml-course-hse

Машинное обучение на ФКН ВШЭ

ml_dm_hse_minor

Репозиторий майнора "Интеллектуальный анализ данных" ФКН НИУ ВШЭ (2016 г.)

ml_investment

Investment tools

mlalgorithms

Minimal and clean examples of machine learning algorithms

mlcourse_open

OpenDataScience Machine Learning course. Both in English and Russian

mlhep2016

Machine Learning in High Energy Physics 2016

mlhep2017

MLHEP 2017 slides & seminars

mth594_machinelearning

The materials for the course MTH 594 Advanced data mining: theory and applications (Dmitry Efimov, American University of Sharjah)

mx14

Short course on nonparametric inference in auditing and litigation, XXIX Foro Internacional de Estadistica, Puebla, MX

numerical-linear-algebra

Free online textbook of Jupyter notebooks for fast.ai Computational Linear Algebra course

numpy

Numpy main repository

practical_dl

DL course co-developed by YSDA, Skoltech and HSE

probabilistic-programming-and-bayesian-methods-for-hackers

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 ;)

pytorch-beginner

pytorch tutorial for beginners

scipy

Scipy library main repository

solidworks-api

C# SolidWorks API stuff

sparse-autoencoder

statsintro_python

Python modules and IPython Notebooks, for the book "Introduction to Statistics With Python"