When one of my favorite independent tech book publishers, No Starch Press, notified me about their new title “Doing Math with Python,” I was energized to review what potentially could be a good new resource for budding data scientists.
I was happy to receive a review copy of book employing a very unique approach for teaching mathematics, “The Manga Guide to Linear Algebra,” published by No Starch Press. This is a comic book, perfect for new data scientists! The book is great for newbies because it clearly spells out each minute step in performing calculations involving vectors, matrices, determinants, linear transformations, kernels, eigenvalues and eigenvectors.
Text analytics recently has become a useful adjunct to other machine learning methods, of great interest to both data scientists and big data engineers. With “Practical Text Analytics: Interpreting text and unstructured data for business intelligence,” Dr. Steven Struhl provides timely and lucid discussion of the topic.
Many times we data scientists, not being statisticians in the strictest sense, hold the fear we may commit some kind of statistical faux paux. Fear no more! With the release of a probing new book “Statistics Done Wrong,” by Alex Reinhart, we have a curious road map for avoiding statistical fallacies.
Download your FREE copy of “Software Defined Storage for Dummies” today, compliments of IBM Platform Computing! This new learning resource can help enterprise thought leaders better understand the new area of software define storage in support of big data initiatives. Software defined storage is a relatively new concept in the computing and storage industry and […]
Download your FREE copy of “Hadoop For Dummies” compliments of IBM Platform Computing! This new learning resource can help enterprise thought leaders better understand the rising importance of big data, especially the Hadoop distributed computing platform. Hadoop for Dummies can help you kick-start your company’s big data initiative.
Sumo Logic, the next generation machine data intelligence company, has announced availability of Transaction Analytics as a component of the Sumo Logic analytics platform to deliver deep visibility into causal relationships across distributed IT systems in order to better inform business decisions.
In this special guest feature, Al Nugent, co-author of the guide “Big Data for Dummies,” looks back at some of the definitions and predictions from the book and see if they still have relevance in today’s technology landscape.
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.”
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.”