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applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

applied-natural-language-processing-w-python

Source Code for 'Applied Natural Language Processing with Python' by Taweh Beysolow II

artificial-intelligence-deep-learning-machine-learning-tutorials

A comprehensive list of Deep Learning / Artificial Intelligence and Machine Learning tutorials - rapidly expanding into areas of AI/Deep Learning / Machine Vision / NLP and industry specific areas such as Automotives, Retail, Pharma, Medicine, Healthcare by Tarry Singh until at-least 2020 until he finishes his Ph.D. (which might end up being inter-stellar cosmic networks! Who knows! 😀)

avenir

Set of Machine Learning and Stochastic Optimazion tools based on Hadoop, Spark and Storm https://pkghosh.wordpress.com/

awesome-courses

List of awesome university courses for learning Computer Science!

awesome-datascience

An awesome Data Science repository to learn and apply for real world problems.

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-rnn

Recurrent Neural Network - A curated list of resources dedicated to RNN

blogfiles

Wordpress Blog Files

caffe

Caffe: a fast open framework for deep learning.

causalimpact

Python Causal Impact port of Google's Algorithm.

cottonwood

A flexible neural network framework for running experiments and trying ideas.

courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

data-algorithms-book

MapReduce and Spark Source Code and Scripts for Data Algorithms Book

data-science-45min-intros

Ipython notebook presentations for getting starting with basic programming, statistics and machine learning techniques

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

data_science_for_economists

Lecture notes for EC 607

data_science_riot

Code examples from the blog www.datascienceriot.com. Mostly sabermetrics and baseball analysis written in R.

datacontract-specification

The Data Contract Specification Repository

datasciencecoursera

DS Track Assignment

datascienceresources

Open Source Data Science Resources.

datasciencespcoursenotes

Compiled Notes for all 9 courses in the Coursera Data Science Specialization

datasharing

The Leek group guide to data sharing

dataviz

deeppy

Deep learning in Python

econml

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

exdata_plotting1

Plotting Assignment 1 for Exploratory Data Analysis

free-data-science-books

Free resources for learning data science

kaggle-criteo

Code for Criteo competition http://www.kaggle.com/c/criteo-display-ad-challenge