M41 Highway

Data science and software engineering blog

List of good books in Big Data

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Data Science is a emerging field comprising of expertise across different domains. Here’s a list of awesome books I highly recommended to individual from different level.

 

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“Software Performance and Scalability – A Quantitative Approach” (Book information)

Author: Henry H. Liu

Performance tuning sometimes is heuristic, particular in large scale Internet system. If you wish to have better planning and get more insight of what the performance characteristics of complicated system, here’s the way you go.

 

 

Image“Algorithms of the Intelligent Web” (Book information)

Authors: Haralambos Marmanis and Dmitry Babenko

This is a very practical book to learn machine learning, data clustering, and other data science topic in a Java programming way. It is especially good for software engineer with Java background as a introductory learning material to get involved in Big Data.

 

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“Python for Data Analysis” (Book Information)

Author: Wes McKinney

There are some very good library for mathematics and statistic in the Python family. If you have programming background, you will love it for its efficiency. This is a very useful book to master Python from a analysis prospective.

 

(I will keep updating the list)

 

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