About the Reviewers

Bill Chambers is a data scientist from the UC Berkeley School of Information. He's focused on building technical systems and performing large-scale data analysis. At Berkeley, he has worked with everything from data science with Scala and Apache Spark to creating online Python courses for UC Berkeley's master of data science program. Prior to Berkeley, he was a business analyst at a software company where he was charged with the task of integrating multiple software systems and leading internal analytics and reporting. He contributed as a technical reviewer to the book Learning Pandas by Packt Publishing.

Alexey Grigorev is a skilled data scientist and software engineer with more than 5 years of professional experience. Currently, he works as a data scientist at Searchmetrics Inc. In his day-to-day job, he actively uses R and Python for data cleaning, data analysis, and modeling. He has contributed as a technical reviewer to other books on data analysis by Packt Publishing, such as Test-Driven Machine Learning and Mastering Data Analysis with R.

Dr. Vahid Mirjalili is a data scientist with a diverse background in engineering, mathematics, and computer science. Currently, he is working toward his graduate degree in computer science at Michigan State University. With his specialty in data mining, he is very interested in predictive modeling and getting insights from data. As a Python developer, he likes to contribute to the open source community. He has developed Python packages, such as PyClust, for data clustering. Furthermore, he is also focused on making tutorials for different directions of data science, which can be found at his Github repository at http://github.com/mirjalil/DataScience.

The other books that he has reviewed include Python Machine Learning by Sebastian Raschka and Python Machine Learning Cookbook by Parteek Joshi. Furthermore, he is currently working on a book focused on big data analysis, covering the algorithms specifically suited to analyzing massive datasets.

Michele Usuelli is a data scientist, writer, and R enthusiast specializing in the fields of big data and machine learning. He currently works for Microsoft and joined through the acquisition of Revolution Analytics, the leading R-based company that builds a big data package for R. Michele graduated in mathematical engineering, and before Revolution, he worked with a big data start-up and a big publishing company. He is the author of R Machine Learning Essentials and Building a Recommendation System with R.