PDF Ebook Data Science on the Google Cloud Platform: Implementing End-to-End Real-Time Data Pipelines: From Ingest to Machine Learning
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Data Science on the Google Cloud Platform: Implementing End-to-End Real-Time Data Pipelines: From Ingest to Machine Learning
PDF Ebook Data Science on the Google Cloud Platform: Implementing End-to-End Real-Time Data Pipelines: From Ingest to Machine Learning
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About the Author
Valliappa (Lak) Lakshmanan is currently a Tech Lead for Data and Machine Learning Professional Services for Google Cloud. His mission is to democratize machine learning so that it can be done by anyone anywhere using Google's amazing infrastructure, without deep knowledge of statistics or programming or ownership of a lot of hardware. Before Google, he led a team of data scientists at the Climate Corporation and was a Research Scientist at NOAA National Severe Storms Laboratory, working on machine learning applications for severe weather diagnosis and prediction.
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Product details
Paperback: 404 pages
Publisher: O'Reilly Media; 1 edition (January 16, 2018)
Language: English
ISBN-10: 1491974567
ISBN-13: 978-1491974568
Product Dimensions:
7 x 0.8 x 9.2 inches
Shipping Weight: 1.4 pounds (View shipping rates and policies)
Average Customer Review:
3.6 out of 5 stars
9 customer reviews
Amazon Best Sellers Rank:
#85,770 in Books (See Top 100 in Books)
Wow. A true tour of data science and engineering on the cloud.It's been a few years since I've worked with tools in this field, but this book was a clear level-headed view for data engineers looking to derive and drive insights from data. Using a core example use case and following it end to end through the entire book (and indeed cloud tools integrated with each other) helped me keep track of what was going on, and kept things from becoming a book on theory rather than one of accomplishment and answers. The purpose and process for each tool was clear, and I also appreciated the explanations of trade-offs and the value added for the choices made. The practice of data science is a LOT easier now with cloud/serverless tools than eight or nine years ago, and I feel this brought me back to the state of the art.
While Lak’s conversational style can be a turn off to some who just want an answer and don’t care about how, I liked this book. Many times with books like this you get an answer or a recipe and you’re done. What happens when your answer or recipe isn’t right for the situation? I’m glad Lak explains his rationale and let’s it be known that there’s more than one way to do it. Could the book have been condensed without the explanations? Yes. Would it have been like almost every other book in the space? Yes. Check out this book if you want a well thought out answer and maybe alternates. If you just want the “right answerâ€, then buy something else.
The book is easy to follow with detailed descriptions of each step followed to build a project from start to end on the Google Cloud Platform.The book is also accompanied by a code repository which lets the readers try out the project themselves.Strongly recommended for data scientists learning to use the platform.
Wonderful book filled with great examples and very engaging writing style! I particularly appreciated how realistic the examples are and was able to use many of the code examples to bootstrap my own projects.
This book was a sad disappointment. The author goes on and on, in long sentences, on unrelated statements instead of addressing the fundamentals of GCP. A waste of time and money. The incentives for publishers to release catchy titles and bloated electronic content on high-priced tags are clear: profits by deception.
Really nice, good price
Very interesting and well written
Very easy to consume because written as a story
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