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538model

538 Election Forecasting Model

advanced-machine-learning-with-python

Code repository for Advanced Machine Learning with Python, published by Packt

advanced-sql-nicar15

Code and data for the NICAR 2015 Advanced SQL with PostgreSQL hands-on class.

algorithm

algorithms

An educational library of algorithms in Python

allstate

Kaggle's Allstate Purchase Prediction Challenge

allstate-1

Kaggle Allstate Prediction Competition

art-r-translation

《R语言编程艺术》翻译项目文件

atap

Code for Applied Text Analysis with Python

awesome

Awesome resources on Bioinformatics, data science, machine learning, programming language (Python, Golang, R, Perl) and miscellaneous stuff.

awesome-python

A curated list of awesome Python frameworks, libraries and software

bank-marketing

bank-marketing-prediction

predict if the client will subscribe a term deposit for bank direct marketing campaign

books

some books

boston-housing-price-predict

With grid search and decision tree.

caltrain-predict

Creating and modelling Caltrain data for improving my colleagues' mental health

cci

Workshop for Deloitte's Center for Customer Insights

clrs

:notebook:Solutions to Introduction to Algorithms

code-test-mysql-python

Code test for an interview

coding-challenge

Challenge for Insight Data Engineering

coding4interviews

A bunch of code about common algorithms / data structures

complete-python-bootcamp

Lectures for Udemy - Complete Python Bootcamp Course

compression-test

Specification of the SPDY protocol

consumer-perception

Personal project to analyze consumer perception of customers

core-python-programming-2nd-edition-examples-and-source-code

Examples and source code from the book

corepython

《Python 核心编程 第二版》 (《Core Python Programming 2nd Edition》) 学习笔记、事例代码以及课后练习

coursera-statistics-one--r

Statistics One is designed to be a comprehensive yet friendly introduction to fundamental concepts in statistics. Comprehensive means that this course provides a solid foundation for students planning to pursue more advanced courses in statistics. Friendly means exactly that. The course assumes very little background knowledge in statistics and introduces new concepts with several fun and easy to understand examples. This course is, quite literally, for everyone. If you think you can't learn statistics, this course is for you. If you had a statistics course before but feel like you need a refresher, this course is for you. Even if you are a relatively advanced researcher or analyst, this course provides a foundation and a context that helps to put one’s work into perspective. Statistics One also provides an introduction to the R programming language. All the examples and assignments will involve writing code in R and interpreting R output. R software is free! What this means is you can download R, take this course, and start programming in R after just a few lectures. That said, this course is not a comprehensive guide to R or to programming in general.

crowdfunding_prediction_recommender

Crowd Funding Success Prediction & recommender system (based Doc2Vec)

cs229-project

Class project for CS 229, Machine Learning at Stanford, 2013

cs570

Code for CS570, Essentials of Data Science