Data Science eBook - 2nd Edition (tentative Table of Content)

Introduction

Part I - Data Science Recipes

  1. New random number generator: simple, strong and fast
  2. Lifetime value of an e-mail blast: much longer than you think
  3. Two great ideas to create a much better search engine
  4. Identifying the number of clusters: finally a solution
  5. Online advertising: a solution to optimize ad relevancy
  6. Example of architecture for AaaS (Analytics as a Service)
  7. Why and how to build a data dictionary for big data sets
  8. Hidden decision trees: a modern scoring methodology
  9. Scorecards: Logistic, Ridge and Logic Regression
  10. Iterative Algorithm for Linear Regression
  11. Approximate Solutions to Linear Regression Problems
  12. Theorems for Traders
  13. Preserving metric and score consistency over time and across clients
  14. Advertising: reach and frequency mathematical formulas
  15. Real Life Example of Text Mining to Detect Fraudulent Buyers
  16. Discount optimization problem in retail analytics
  17. Sales forecasts: how to improve accuracy while simplifying models?
  18. How could Amazon increase sales by redefining relevancy?
  19. How to build simple, accurate, data-driven, model-free confidence i...
  20. Comprehensive list of Excel errors, inaccuracies and use of non-sta...
  21. 10+ Great Metrics and Strategies for Email Campaign Optimization
  22. 10+ Great Metrics and Strategies for Fraud Detection
  23. Case Study: Four different ways to solve a data science problem
  24. Case Study: Email marketing - †analytic tips to boost performance b...
  25. Optimize keyword campaigns on Google in 7 days: an 11-step procedure
  26. How do you estimate the proportion of bogus accounts on Facebook?
  27. Stat models to solve astronomical mysteries - application to business data
  28. How to detect a pattern? Problem and solution
  29. From chaos to clusters - statistical modeling without models
  30. Simple solutions to make videos with R
  31. Three classes of metrics: centrality, volatility, and bumpiness
  32. How to optimize email campaigns? Part I
  33. Simple steps to increase speed of web crawling by a factor 80,000
  34. How are database joins optimized? How can you do better to handle big data?
  35. Correlation vs. causation
  36. Seven tricky sentences for NLP and text mining algorithms
  37. Great statistical analysis: forecasting meteorite hits
  38. Fast clustering algorithms for massive datasets
  39. How are hotel room rates determined
  40. The curse of big data
  41. Simple technique to improve poor predictive models
  42. Simple source code to simulate nice cluster structures
  43. Source code for our Big Data keyword correlation API
  44. Correlation vs. causation
  45. Shootings stars: producing videos about data

Part II - Data Science Discussions

  1. Statisticians Have Large Role to Play in Web Analytics (AMSTAT inte...
  2. Future of Web Analytics: Interview with Dr. Vincent Granville
  3. Connecting with the Social Analytics Experts
  4. Interesting note and questions on mathematical patents
  5. Big data versus smart data: who will win?
  6. Creativity vs. Analytics: Are These Two Skills Incompatible?
  7. Barriers to hiring analytic people
  8. Salary report for selected analytical job titles
  9. Are we detailed-oriented or do we think "big picture", or both?
  10. Why you should stay away from the stock market
  11. Gartner Executive Programs' Worldwide Survey of More Than 2,300 CIOs
  12. 4.4 Million New IT Jobs Globally to Support Big Data By 2015
  13. One Third of Organizations Plan to Use Cloud Offerings to Augment BI Capabilities
  14. Twenty Questions about Big Data and Data Sciences
  15. Interview with Drew Rockwell, CEO of Lavastorm
  16. Can we use data science to measure distances to stars?
  17. Eighteen questions about real time analytics
  18. Can any data structure be represented by one-dimensional arrays?
  19. Data visualization: example of a great, interactive chart
  20. Data science jobs not requiring human interactions
  21. Featured Data Scientist: Vincent Granville, Analytic Entrepreneur
  22. Healthcare fraud detection still uses cave-man data mining techniques
  23. Why are spam detection algorithms so terrible?
  24. What is a Data Scientist?
  25. Twenty seven types of data scientists: †where do you fit?
  26. Seven tricky sentences for NLP and text mining algorithms
  27. How maths should be taught in high school
  28. An alternative to FICO scores?
  29. Shopper Alert: Price May Drop for You Alone | NewYorkTimes
  30. Vertical vs. Horizontal Data Scientists
  31. 14 questions about data visualization tools
  32. New, fast Excel to process billions of rows via the cloud
  33. When data flows faster than it can be processed
  34. Car accident statistics by profession
  35. Extreme Data Science
  36. Six keywords characterizing milestones in the history of analytic engineering: from 1988 to 2033
  37. A new idea for an analytic business startup
  38. Four innovative ideas to optimize business processes
  39. Vincent's answers to data science questions - Part 2
  40. How do data scientists rank?
  41. History, Evolution and Classification of Programming Languages
  42. Automated news feed optimization
  43. Shopper Alert: Price May Drop for You Alone
  44. Why are clinical trials failing?
  45. Is Algebra Necessary? | New York Times
  46. The 8 worst predictive modeling techniques
  47. What are the most difficult things to predict?
  48. Fake Data Science
  49. Analytics{Benzene} => {big Pharma, Nanotechnologies}
  50. What MapReduce can't do
  51. Big Data startup to fix healthcare
  52. How to reverse-engineer Google?

Part III - Data Science Resources

  1. Vincentís list
  2. History of 24 analytic companies over the last 30 years
  3. Fifteen great data science articles from influential news outlets
  4. List of publicly traded analytic companies
  5. Thirty unusual applications of data sciences, analytics and big data
  6. 50 unusual ways analytics are used to make our lives better
  7. Berkeley course on Data Science
  8. Over 5,000,000 financial, economic and social datasets
  9. Map of Data Science University Programs
  10. 27 criteria to choose analytic tools
  11. Resources
  12. 50 big data events scheduled worldwide in May 2012
  13. Top analytic blogs and websites, with trending information
  14. 86 Helpful Tools for the Data Professional
  15. List of Free Statistical Software Packages
  16. List of programming languages
  17. Sample proposal for a data science / big data project
  18. Password and hijacked email dataset for you to test your data science skills
  19. Data Science Tools
  20. Data Science Dictionary
  21. Salary/Income of Analytics/Data Mining/Data Science professionals
  22. 66 job interview questions for data scientists
  23. Proposal for an Apprenticeship in Data Science