Statistical Case Studies — from a Data Science Perspective

Time and Venue

• Every Thursday 10:00 — 12: 35 from February 28 to June 25, 2018
• Room 101, Building 6, Shahe Campus

Prerequisites

• Basic knowledge of statistics
• Basic knowledge of computing

Part I: Tools for Data Processing

1. Introduction to Data Processing Tools
   • Python-from-Scratch.ipynb | PDF
   • Python Style Guide
2. Data and Statistical Modelling with Python
   • Python-Data-Structures.ipynb | PDF
   • Python-for-Statistical-Modeling | PDF
3. Natural Language Processing
   • Python-and-Texts.ipynb | PDF
   • Python-and-Text-Processing.ipynb | PDF
4. Chinese Text Processing | PDF
5. Web Scraping with Python
   • Web Scraping with BS4 and Scrapy | HTML | Code
   • Selenium | HTML
6. Guest Lecture: TBA

Part II: Models

1. Sentiment and Semantic Analysis
   • Text Feature Extraction | HTML | DATA
2. Probabilistic Methods for Modelling Texts
   • Word Vectors | HTML | SLIDES
   • Word2Vec | Related Papers [1] [2]
   • Probabilistic Topic Models | HTML | SLIDES
3. Methods for mixed types of data
4. Guest Lecture: TBA

Part III: Reporting

1. Visualization Tools | HTML
2. Guest Lecture: TBA
3. Presentation
4. Final Assignments