Reading plans

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It’s important to keep yourself updated in this data science area. So I did some research and got a book list on some topics I interested in.

  • Data Visualization

  1. The Visual Display of Quantitative Information Bought the book already, need to dig into the topic.  About the book: Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis.
  2. Now you see it Luckily this book is here, in my office! Maybe good for business analyses.
  3. Interactive Data Visualization for the Web This book has a nice online book for people to learn D3 interactively. I already read several chapters.
  4. Storytelling with Data Got this book during my last job. It contains not just how to make pretty and efficient graphs, but also how to present your data analyses results. Since I want to develop a related course on data visualization and presentation, I may need to read this book as a whole.

  • R skills

  1. Hands-on programming with R Very basic R. Since I’m teaching R in NYCDSA now, this book helps me a lot. Planning to go over this book very quickly.
  2. Efficient R programming It’s important to program efficiently. This book is relevant new.
  3. R for Data Science Another basic book. As I said, reading these old topics can help me teach and renew my memory.

  4. Advanced R  The book is designed primarily for R users who want to improve their programming skills and understanding of the language.

  • Machine Learning

  1. A Handbook of Statistical Analyses using R A great book! It contains all the R code and related interpretation. Also, a related R package!!
  2. General Idea of deep learning https://www.quora.com/What-are-your-recommendations-for-self-studying-machine-learning/answer/Yann-LeCun
  3. H2O related packages
  4. The Elements of Statistical Learning Need to go over from chapter to chapter! Every time I read some from the book, I feel so fresh.

Analysis on the supplier diversity of J&J’s pharmaceutical companies using Bayesian network

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Introduction The purpose of this report is to identify the relationships in the supplier base at Johnson & Johnson, especially the business arrangements with minority and women-owned companies. I chose the three pharmaceutical companies’ data, which contains 28 variables of eight departments’ purchase records (n=725,414). To prepare for the data analysis, this paper combined the […]