Practical Data Science with Python: Learn tools and techniques from hands-on examples to extract insights from data

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Practical Data Science with Python: Learn tools and techniques from hands-on examples to extract insights from data Customer Reviews

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• 5.0 out of 5 stars from Gabe Rigall -- Just The Right Amount of Data Science : BLUF: If you want to get into Data Science but are put off by the staggering amount of information out there, this book is for you. ( Reviewed in the United States on October 20, 2021 )
• 4.0 out of 5 stars from Blaine Bateman -- Covers the entirety of Data Science : The author Nathan George takes on a big task with this book, and does a good job executing it. Data Science is a very broad topic. In addition, it inevitably overlaps into Software Engineering, Computer Programming, Cloud Compute, and many other topics. After a whirlwind review of the history of Data Science, tools, specializations, and project structure, the book moves right into installing and using Python. As the book is targeted at relative newcomers to Data Science as well as those interested to change careers, this makes sense, as the audience might know another language or analytics platform, and face a learning curve with Python. I especially liked the inclusion of CRISP-DM and TDSP in the introduction, as beginning a project with a good structure is an important success factor, and both of these frameworks, one older and long-proven, and the other a more modern adaptation, can and should be used in a majority of projects. ( Reviewed in the United States on October 19, 2021 )
• 4.0 out of 5 stars from Naomi Ceder -- Good compendium for intermediate level, not for beginners : (Disclaimer: I was asked to review this book by the publisher, but otherwise have no connection with the author or publisher.) ( Reviewed in the United States on October 21, 2021 )

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