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2014

Official content for the Fall 2014 Harvard CS109 Data Science course

2014_data

Data directory for the CS109 Data Science course

2015

Public material for CS109

2015lab1

2015lab10

2015lab11

Overview of a project: Food Inspection Forecasting

2015lab2

2015lab3

2015lab4

Lab for Linear and Logistic Regression, SciKit Learn

2015lab5

Lab 5, the first on Machine Learning!

2015lab6

2015lab7

Decison Trees, Random Forrests, Ensemble Methods

2015lab8

AWS, Vagrant, and Spark

2015lab9

awesome-artificial-intelligence

A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers

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-rl

Reinforcement learning resources curated

awesome-robotics

A curated list of awesome links and software libraries that are useful for robots.

birthday-greetings-kata

Sources and docs for a simple refactoring and OO design exercise

com.vogella.tutorials.eclipse

com.vogella.tutorials.java

com.vogella.tutorials.web

content

Official content for Harvard CS109

cookbook-2nd-code

Code of the IPython Cookbook, Second Edition, by Cyrille Rossant, Packt Publishing 2018 [read-only repository]

courseware

Courseware VM images and instructions

cppcoreguidelines

The C++ Core Guidelines are a set of tried-and-true guidelines, rules, and best practices about coding in C++

cs109_data

Datasets for CS109

dat8

General Assembly's Data Science course in Washington, DC

data-science-ipython-notebooks

Recently updated with 50 new 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.