Building the Data Lakehouse (Technics Publications)
Friday, 01 October 2021

This book describes the features and architecture of the data lakehouse, along with its analytical infrastructure; the next generation of the data warehouse and data lake. Bill Inmon, Mary Levins and Ranjeet Srivastava describe how data lakehouses are designed for use with analytics, machine learning, and data science and also discuss how the universal common connector blends structured, textual, analog, and IoT data.

<ASIN:1634629663>

 

Author: Bill Inmon, Mary Levins and Ranjeet Srivastava
Publisher: Technics Publications
Date: October 2021
Pages: 254
ISBN: 978-1634629669
Print: 1634629663
Kindle: ‎ B09GRZ9KP3
Audience: data scientists
Level: Intermediate
Category: Data Science

For recommendations of Big Data books see Reading Your Way Into Big Data in our Programmer's Bookshelf section.

 

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CSS In Easy Steps 4th Ed

Author: Mike McGrath
Publisher: Easy Steps
Pages: 192
ISBN: 978-1840788754
Print: 1840788755
Kindle: B083ZJD91Z
Audience: CSS beginners
Rating: 5
Reviewed by: David Conrad

If you are looking for a simple beginner's introduction to CSS then this book fits the bill.



Foundations of Deep Reinforcement Learning

Authors: Laura Graesser and Wah Loon Keng
Publisher: Addison-Wesley
Pages: 416
ISBN: 978-0135172384
Print: 0135172381
Kindle: B07ZVYZC6F
Audience: Developers in machine learning
Rating: 5
Reviewer: Mike James
Reinforcement learning seems to be able to do anything if you approach it in the right way, but [ ... ]


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