Download PDF Head Gardeners

Download PDF Head Gardeners

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Head Gardeners

Download PDF Head Gardeners

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Review

Winner of the Garden Media Guild Best Inspirational Book Award 2017

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About the Author

Ambra Edwards is the author of Gardening in a Changing Climate. A regular contributor to the Guardian, the Telegraph, Gardens Illustrated and Country Living, she has twice been awarded the title of Garden Journalist of the Year by the Garden Media Guild. Charlie Hopkinson is a portrait and landscape photographer specializing in the arts, gardening and landscape.

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Product details

Hardcover: 240 pages

Publisher: Pimpernel Press (November 1, 2017)

Language: English

ISBN-10: 1910258741

ISBN-13: 978-1910258743

Product Dimensions:

6.8 x 0.8 x 9 inches

Shipping Weight: 1.6 pounds (View shipping rates and policies)

Average Customer Review:

5.0 out of 5 stars

4 customer reviews

Amazon Best Sellers Rank:

#142,825 in Books (See Top 100 in Books)

SO well written, I cou.d not put it down. Inspiring as well.

Great book. Very interesting and insightful stories of head gardeners. It is an enjoyable read.

Always enjoy learning about how people develop their gifts.

This is a delightful book. As a garden design junkie I look at lots of gardens and it is fascinating to read about the people who make them.The Garden of Cosmic Speculation has been created with a man who has been at the garden 50 years and has been a full partner in making it happen.Sissinghurst is famous and it is being loved to death and it's head gardener is trying to bring back Vita's romantic spirit. These are just 2 of 13 famous gardens whose head gardeners are profiled. They each have a different story. If you love gardens especially English ones this is a great book to read.

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PDF Ebook Data Analytics with Hadoop: An Introduction for Data Scientists

PDF Ebook Data Analytics with Hadoop: An Introduction for Data Scientists

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Data Analytics with Hadoop: An Introduction for Data Scientists

PDF Ebook Data Analytics with Hadoop: An Introduction for Data Scientists

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About the Author

Benjamin Bengfort is a Data Scientist who lives inside the beltway but ignores politics (the normal business of DC) favoring technology instead. He is currently working to finish his PhD at the University of Maryland where he studies machine learning and distributed computing. His lab does have robots (though this field of study is not one he favors) and, much to his chagrin, they seem to constantly arm said robots with knives and tools; presumably to pursue culinary accolades. Having seen a robot attempt to slice a tomato, Benjamin prefers his own adventures in the kitchen where he specializes in fusion French and Guyanese cuisine as well as BBQ of all types. A professional programmer by trade, a Data Scientist by vocation, Benjamin's writing pursues a diverse range of subjects from Natural Language Processing, to Data Science with Python to analytics with Hadoop and Spark.Jenny Kim is an experienced big data engineer who works in both commercial software efforts as well as in academia. She has significant experience in working with large scale data, machine learning, and Hadoop implementations in production and research environments. Jenny (with Benjamin Bengfort) previously built a large scale recommender system that used a web crawler to gather ontological information about apparel products and produce recommendations from transactions. Currently, she is working with the Hue team at Cloudera, to help build intuitive interfaces for analyzing big data with Hadoop.

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Product details

Paperback: 288 pages

Publisher: O'Reilly Media; 1 edition (June 18, 2016)

Language: English

ISBN-10: 9781491913703

ISBN-13: 978-1491913703

ASIN: 1491913703

Product Dimensions:

6.8 x 0.6 x 9.2 inches

Shipping Weight: 1 pounds (View shipping rates and policies)

Average Customer Review:

4.0 out of 5 stars

5 customer reviews

Amazon Best Sellers Rank:

#412,332 in Books (See Top 100 in Books)

Be prepared to spend a lot of time debugging their sample code and the installation instructions for the various software packages. Most of the examples in the book do not match the sample code or data provided. And much of what they refer to in the book is not included in the samples. On top of all this, they even manage to mangle their examples just within the book itself. As an example, they walk through a data exercise first using mapreduce. Then they try to do the same thing using spark. But the spark program produces incorrect results. Yes, it works, but it isn't what mapreduce produced, or the book claimed was the expected output.On the plus side, the best way to learn something is by doing and this book will give you plenty of opportunities to figure things out on your own. That's always a plus. But not for the authors.

Best buy!

Good book to start Big Data with.

I really like this book. It is a great overview of a plethora of topics around doing scalable data analytics and data science. It is extremely up-to date, going through techniques that have existed for many years now like MapReduce, but also newer systems like Spark, all in the context of the Hadoop eco-system. They go into machine learning techniques, data management, and overall paint a nice picture around what data science is, and why data products are important, while teaching you how to make them!Every single concept is explained in a clear and concise manner, and wherever details are omitted there is always a citation to a source where the reader can continue reading more about it, which I think is great. Although I wouldn’t classify myself as a beginner, I believe it is friendly to both professionals and beginners, as it is centered around python which makes most examples (that are conveniently uploaded in a nice github repository) really easy to simply run and play around with. After describing something, whether that would be a technique for data analysis, or just the in-and outer workings of some analysis platform like HBase, Hive etc, the authors provide examples so that while you’re reading about this stuff you can also run it, play around with it and really explore how these systems function; I believe this is a crucial part of familiarizing ones’ self with new platforms.Another thing I enjoyed a lot was the ending of this book. After you really dive into all of these systems and get your feet wet with each one of them, the authors wrap it all up in a nice bow by taking a step back and describing the entire end-to-end process of how you would go about productively using the knowledge you’ve gotten from this book to build data analytics workflows!I highly recommend this to anyone who both knows that they want to learn how to deploy scalable analytics workflows in 2016, but also to readers who are simply just curious about data science; this book will suck you in!

Really nice textbook to work and learn hadoop systems and Mapreduce.

Data Analytics with Hadoop: An Introduction for Data Scientists PDF
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Data Analytics with Hadoop: An Introduction for Data Scientists PDF

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Data Analytics with Hadoop: An Introduction for Data Scientists PDF

Data Analytics with Hadoop: An Introduction for Data Scientists PDF

Ebook Free , by モトイ・トクメイ（基・督命）

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, by モトイ・トクメイ（基・督命）

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Product details

File Size: 2218 KB

Print Length: 119 pages

Simultaneous Device Usage: Unlimited

Publication Date: March 12, 2019

Sold by: Amazon Digital Services LLC

Language: Japanese

ASIN: B07PPC1YQC

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Amazon Best Sellers Rank:

#1,447,294 Paid in Kindle Store (See Top 100 Paid in Kindle Store)

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