Ebook Free Learning PySpark, by Tomasz Drabas, Denny Lee
As understood, numerous people say that publications are the home windows for the world. It does not indicate that getting e-book Learning PySpark, By Tomasz Drabas, Denny Lee will indicate that you could purchase this world. Just for joke! Reading an e-book Learning PySpark, By Tomasz Drabas, Denny Lee will opened up a person to believe better, to keep smile, to delight themselves, as well as to motivate the understanding. Every publication also has their characteristic to influence the reader. Have you known why you review this Learning PySpark, By Tomasz Drabas, Denny Lee for?
Learning PySpark, by Tomasz Drabas, Denny Lee
Ebook Free Learning PySpark, by Tomasz Drabas, Denny Lee
Learning PySpark, By Tomasz Drabas, Denny Lee. Discovering how to have reading behavior is like learning to attempt for eating something that you truly don't desire. It will certainly need more times to aid. In addition, it will additionally little force to serve the food to your mouth and also ingest it. Well, as checking out a book Learning PySpark, By Tomasz Drabas, Denny Lee, occasionally, if you should review something for your brand-new jobs, you will feel so woozy of it. Even it is a publication like Learning PySpark, By Tomasz Drabas, Denny Lee; it will certainly make you really feel so bad.
Right here, we have many e-book Learning PySpark, By Tomasz Drabas, Denny Lee as well as collections to check out. We likewise serve alternative kinds as well as kinds of the books to search. The fun publication, fiction, past history, novel, science, and also various other kinds of books are offered right here. As this Learning PySpark, By Tomasz Drabas, Denny Lee, it comes to be one of the preferred book Learning PySpark, By Tomasz Drabas, Denny Lee collections that we have. This is why you are in the best site to view the remarkable publications to possess.
It won't take even more time to purchase this Learning PySpark, By Tomasz Drabas, Denny Lee It won't take even more cash to publish this e-book Learning PySpark, By Tomasz Drabas, Denny Lee Nowadays, individuals have actually been so wise to use the modern technology. Why don't you use your gadget or other device to conserve this downloaded and install soft documents book Learning PySpark, By Tomasz Drabas, Denny Lee Through this will let you to always be accompanied by this e-book Learning PySpark, By Tomasz Drabas, Denny Lee Certainly, it will certainly be the finest pal if you review this book Learning PySpark, By Tomasz Drabas, Denny Lee till finished.
Be the very first to purchase this book now and also get all factors why you have to review this Learning PySpark, By Tomasz Drabas, Denny Lee Guide Learning PySpark, By Tomasz Drabas, Denny Lee is not simply for your responsibilities or need in your life. Publications will constantly be a great close friend in every time you check out. Now, allow the others learn about this web page. You can take the perks and also discuss it likewise for your close friends and also individuals around you. By through this, you can truly obtain the significance of this e-book Learning PySpark, By Tomasz Drabas, Denny Lee profitably. What do you consider our suggestion below?
Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0
About This Book- Learn why and how you can efficiently use Python to process data and build machine learning models in Apache Spark 2.0
- Develop and deploy efficient, scalable real-time Spark solutions
- Take your understanding of using Spark with Python to the next level with this jump start guide
If you are a Python developer who wants to learn about the Apache Spark 2.0 ecosystem, this book is for you. A firm understanding of Python is expected to get the best out of the book. Familiarity with Spark would be useful, but is not mandatory.
What You Will Learn- Learn about Apache Spark and the Spark 2.0 architecture
- Build and interact with Spark DataFrames using Spark SQL
- Learn how to solve graph and deep learning problems using GraphFrames and TensorFrames respectively
- Read, transform, and understand data and use it to train machine learning models
- Build machine learning models with MLlib and ML
- Learn how to submit your applications programmatically using spark-submit
- Deploy locally built applications to a cluster
Apache Spark is an open source framework for efficient cluster computing with a strong interface for data parallelism and fault tolerance. This book will show you how to leverage the power of Python and put it to use in the Spark ecosystem. You will start by getting a firm understanding of the Spark 2.0 architecture and how to set up a Python environment for Spark.
You will get familiar with the modules available in PySpark. You will learn how to abstract data with RDDs and DataFrames and understand the streaming capabilities of PySpark. Also, you will get a thorough overview of machine learning capabilities of PySpark using ML and MLlib, graph processing using GraphFrames, and polyglot persistence using Blaze. Finally, you will learn how to deploy your applications to the cloud using the spark-submit command.
By the end of this book, you will have established a firm understanding of the Spark Python API and how it can be used to build data-intensive applications.
Style and approachThis book takes a very comprehensive, step-by-step approach so you understand how the Spark ecosystem can be used with Python to develop efficient, scalable solutions. Every chapter is standalone and written in a very easy-to-understand manner, with a focus on both the hows and the whys of each concept.
- Sales Rank: #165382 in Books
- Published on: 2017-02-27
- Released on: 2017-02-27
- Original language: English
- Dimensions: 9.25" h x .62" w x 7.50" l,
- Binding: Paperback
- 274 pages
About the Author
Tomasz Drabas is a Data Scientist working for Microsoft and currently residing in the Seattle area. He has over 13 years of experience in data analytics and data science in numerous fields: advanced technology, airlines, telecommunications, finance, and consulting he gained while working on three continents: Europe, Australia, and North America. While in Australia, Tomasz has been working on his PhD in Operations Research with a focus on choice modeling and revenue management applications in the airline industry. At Microsoft, Tomasz works with big data on a daily basis, solving machine learning problems such as anomaly detection, churn prediction, and pattern recognition using Spark. Tomasz has also authored the Practical Data Analysis Cookbook published by Packt Publishing in 2016.
Denny Lee
Denny Lee is a Principal Program Manager at Microsoft for the Azure DocumentDB team Microsoft's blazing fast, planet-scale managed document store service. He is a hands-on distributed systems and data science engineer with more than 18 years of experience developing Internet-scale infrastructure, data platforms, and predictive analytics systems for both on-premise and cloud environments. He has extensive experience of building greenfield teams as well as turnaround/ change catalyst. Prior to joining the Azure DocumentDB team, Denny worked as a Technology Evangelist at Databricks; he has been working with Apache Spark since 0.5. He was also the Senior Director of Data Sciences Engineering at Concur, and was on the incubation team that built Microsoft's Hadoop on Windows and Azure service (currently known as HDInsight). Denny also has a Masters in Biomedical Informatics from Oregon Health and Sciences University and has architected and implemented powerful data solutions for enterprise healthcare customers for the last 15 years.
Most helpful customer reviews
See all customer reviews...Learning PySpark, by Tomasz Drabas, Denny Lee PDF
Learning PySpark, by Tomasz Drabas, Denny Lee EPub
Learning PySpark, by Tomasz Drabas, Denny Lee Doc
Learning PySpark, by Tomasz Drabas, Denny Lee iBooks
Learning PySpark, by Tomasz Drabas, Denny Lee rtf
Learning PySpark, by Tomasz Drabas, Denny Lee Mobipocket
Learning PySpark, by Tomasz Drabas, Denny Lee Kindle
Tidak ada komentar:
Posting Komentar