casssini Goto Github PK

acai

Code for "Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer"

annoy

Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk

another-python-tutorial

🐍3

awesome-computer-vision

A curated list of awesome computer vision resources

awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

awesome-machine-learning

A curated list of awesome Machine Learning frameworks, libraries and software.

awesome-machine-learning-on-source-code

Interesting links & research papers related to Machine Learning applied to source code

awesome-nlp

:book: A curated list of resources dedicated to Natural Language Processing (NLP)

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

awesome-rl

Reinforcement learning resources curated

aws-machine-learning-university-accelerated-nlp

Machine Learning University: Accelerated Natural Language Processing Class

coursera_reinforcement_learning

Coursera Reinforcement Learning Specialization by University of Alberta & Alberta Machine Intelligence Institute

data-science-from-scratch

code for Data Science From Scratch book

data-scientist-books

Data-Scientist-Books (Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Long Short Term Memory, Generative Adversarial Network, Time Series Forecasting, Probability and Statistics, and more.)

data_mining_in_action_2017

dealing_with_data

Material that I use for a variety of classes and tutorials

deeplearning.ai

Materials from deeplearning.ai course on Coursera

dmia2018_fall_public

dmia_base_2019_autumn

dmia_dl_2019_autumn

dmia_industry_2019_autumn

dmia_sport_2019_autumn

Репозиторий спортивного направления DMIA, осень 2019

dmia_sport_2019_spring

Репозиторий спортивного направления DMIA, весна 2019

easy-pi

:sunglasses: Материалы для успешного прохождения курсов на Бакалаврской программе «Программная инженерия» НИУ ВШЭ

effective-pandas

Source code for my collection of articles on using pandas.

examples

The course examples are organised in folders.

grin

GRIN is a compiler back-end for lazy and strict functional languages with whole program optimization support.

hse-shad-ml

:mortar_board: Введение в машинное обучение. Курс от ВШЭ и ШАД на coursera.org

iml

Курс "Введение в машинное обучение" (ВМК, МГУ имени М.В. Ломоносова)

jupyter

Jupyter metapackage for installation, docs and chat