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:date: :pencil2: A/B Testing / Analysing the effect of 'free trial period' for Udacity students to measure whether they enroll or continue to finish a course or not
Empirical quantitative marketing models for PhD level marketing students
37902 Advanced Quantitative Marketing - Pradeep Chintagunta
:memo: An awesome Data Science repository to learn and apply for real world problems.
Introduce necessary Bayesian and numerical knowedge required to PhD students in Economics and Quantitative Marketing
code for numerically solving dynamic programming problems
BLP-Python provides an implementation of random coefficient logit model of Berry, Levinsohn and Pakes (1995)
:bar_chart: Path to a free self-taught education in Data Science!
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.
:baseball: :bar_chart: D3 - Visualization/ In this project I perform an explanatory data analysis on performance of baseball players based on their weight, height and handedness
:house_with_garden: :traffic_light: Python - SQL / Wrangling and cleaning up the OpenStreeMap data from San Francisco area and running queries on it using SQL
A collection of interesting dynamic programming problems
Recreation of a dataset similar to Guadagni and Little 1983, and estimation of the parameters using a custom implementation of mixed logit
Here you will find the files for an assignment I completed with another student for a graduate level Industrial Organization course. The assignment replicates parts of John Rust's 1987 paper "Optimal Replacement of GMC Bus Engines: An Empirical Model of Harold Zucher" published in Econometrica Vol. 55, No. 5.
a D3.js tutorial
Recreation of the "Optimal Replacement of GMC Bus Engines" paper by J. Rust, describing a single-agent dynamic optimization model.
Open Content for self-directed learning in data science
Content for Udacity's Machine Learning curriculum
A tutorial of machine learning using R.
machine learning and deep learning tutorials, articles and other resources
Basic Machine Learning and Deep Learning
Google Chrome, Firefox, and Thunderbird extension that lets you write email in Markdown and render it before sending.
The code for the paper "Constrained Optimization Approaches To Estimation Of Structural Models: Comment" by Iskhakov, Lee, Rust, Schjerning and Seo. Econometrica, 2015.
nlp相关实验
NYC Citi Bike system data and analysis
Wrangling and Analysis with Python and SQL
The "Python Machine Learning" book code repository and info resource
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.