This is an announcement regarding my upcoming book: Data Science 2.0. The subtitle is Automation, survival kit, career resources.
Just like our first book, it will first be available as a free PDF document to members of our community. It will feature
- new robust techniques for data science automation and black-box analytics
- survival kit (the data science cheat sheet)
- detailed source code for several of the core techniques published in our first book (for instance hidden decision trees, combinatorial multivariate feature optimization, predictive analytics power and other synthetic metrics, model-free confidence intervals), as well as for newly introduced techniques such as Jackknife regression
- career resources (definition of big data, what is data science, why is it different, geographic distribution of data scientists, data science sub-domains, journey and passions of a data scientist, trends and skill clusters based on NLP of our data scientist member database)
- fun stuff such as our data science challenges, or data visualized with a video (with R source code to produce the video)
- discussion of interesting problems (law of series, Zipf distribution, data compression fundamental result, Twitter app to detect thought leaders)
- case studies, how to do better data science with success stories explained in details (data science from the trenches, creating bias-free scoring engines, creating sound relevancy engines, eliminate bogus reviews and bogus web traffic)
- smart light analytics and even simple Excel spreadsheets, metrics and strategies that outperforms raw, heavy analytic artillery or advanced statistical modeling - even on big data
- selection of R, Python, machine learning, Hadoop, visualization and other resources
You can already have a peek at the content, by clicking here and looking at the double-starred articles: they will be incorporated in our new book. I will complete the listing (of contributions to be added to our new book, the double-starred articles) in the next few weeks. For recent articles to be added to Data Science 2.0, click here. A link to the eBook (once the first draft is completed) will be provided here. So bookmark this page!
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