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Book Reviews: The Bootstrap Resampling Technique

In the spirit of the importance of bootstrap methods to contemporary machine learning, I’d like to review several prominent books on the subject. Some of the titles are relatively new, while others can be considered “classics.”

Book Review: Feynman Lectures on Computation

True to form as the original “curious character,” legendary physicist Richard Feynman often broke out of his favored field of expertise to give his own special slant on other areas. One important case in point was when he gave a course at Caltech from 1983-1986 called “Potentialities and Limitations of Computing Machines.”

Book Review: Think Bigger

In “Think Bigger: Developing a Successful Big Data Strategy for Your Business” (AMACOM, April 2014), author Mark van Rijmenam offers real-world insights and clear explanations to make getting a firm grasp on Big Data manageable for business leaders at all levels, in companies of all sizes and shapes.

Data Science 101: The Data Analytics Handbook

“Data Analytics Handbook” is a new resource meant to inform young professionals about the field of data science. Written by a group of students at UC Berkeley: Brian Liou, Tristan Tao, and Elizabeth Lin. Edition One of the book includes in-depth interviews with Data Scientists & Data Analysts.

Book Review: Data Crush

A new book came across my desk the other day that I really enjoyed in terms of its timeliness for the audience of Big Data decision makers trying to make sense of this new technology. “Data Crush – How the Information Tidal Wave is Driving New Business Opportunities,” by Christopher Surdak aims to spark a widespread business movement beyond the pressing goal of surviving the data tsunami.

Data Science 101: Deep Learning Methods and Applications

Microsoft Research, the research arm of the software giant, is a hotbed of data science and machine learning research. Microsoft has the resources to hire the best and brightest researchers from around the globe. A recent publication is available for download (PDF): “Deep Learning: Methods and Applications” by Li Deng and Dong Yu, two prominent researchers in the field.

Book Review: Big Data Marketing by Lisa Arthur

I’ve been promoting the concept of Computational Marketing for some time here on insideBIGDATA and elsewhere because it is quite clear that modern marketing is nothing without data. So it’s great to see a new book aligned with this notion – Big Data Marketing by Lisa Arthur. The data driven movement is marching forward at […]

Introduction to Data Science – Free eBook

A new free eBook became available: Introduction to Data Science by Jeffrey Stanton, Associate Professor at Syracuse University. This book provides non-technical readers with a gentle introduction to essential concepts and activities of data science.

Book Review: Doing Data Science

O’Reilly Media does it right. Their PR department gives valuable support to the grassroots efforts in the data science community by helping out local Meetup groups. A case in point is how they provided a number of current titles to be given away as raffle prizes for the Los Angeles R User Group of which […]

Book Review: Machine Learning for Hackers

It isn’t often that I get excited about a book in my field of data science, but I must admit that I was highly energized the first time I thumbed through a new copy of Machine Learning for Hackers by Drew Conway and John Myles White courtesy of O’Reilly Media. This is not a reference […]