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awesome-deep-learning

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

catboost

CatBoost is an open-source gradient boosting on decision trees library with categorical features support out of the box for Python, R

clairvoyant

Software designed to identify and monitor social/historical cues for short term stock movement

d2l-en

Dive into Deep Learning, Berkeley STAT 157 (Spring 2019) textbook. With code, math, and discussions.

daft

Render some probabilistic graphical models using matplotlib

deep-learning-keras-euroscipy2016

# Deep Learning with Keras

fasttext

Library for fast text representation and classification.

filterpy

Python Kalman filtering and optimal estimation library. Implements Kalman filter, particle filter, Extended Kalman filter, Unscented Kalman filter, g-h (alpha-beta), least squares, H Infinity, smoothers, and more. Has companion book 'Kalman and Bayesian Filters in Python'.

framework

Machine learning, computer vision, statistics and general scientific computing for .NET

hurdledmr.jl

Hurdle Distributed Multiple Regression (HDMR) implemented in Julia

idtxl

jf2016-skggm

Tutorials to estimate inverse covariance matrices using the skggm package

kaggle_stocks

R scripts for taking a crack at The Winton Stock Market Challenge on kaggle.com

kagglelib

A library of most useful basic functions for Kaggle competitions.

lightgbm

LightGBM is a fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

machine-learning-tutorials

machine learning and deep learning tutorials, articles and other resources

mobius

C# language binding and extensions to Apache Spark

moe

A global, black box optimization engine for real world metric optimization.

mxnet

Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more

net2net

numpy implementation of net 2 net from the paper Net2Net: Accelerating Learning via Knowledge Transfer http://arxiv.org/abs/1511.05641

nevergrad

A Python toolbox for performing gradient-free optimization

nlp-progress

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

numsharp

NumPy + SciPy in .NET Core. Tensor computation library used by other SciSharp projects.

opera

Online Prediction by ExpeRt Aggregation

paddle

PArallel Distributed Deep LEarning

pandas.net

Pandas port in C#, data analysis tool.

paratext

A library for reading text files over multiple cores.

particles

Sequential Monte Carlo in python

pomegranate

Fast, flexible and easy to use probabilistic modelling in Python.

pycma

Python implementation of CMA-ES