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You're reading from  Large Scale Machine Learning with Python

Product typeBook
Published inAug 2016
Reading LevelIntermediate
PublisherPackt
ISBN-139781785887215
Edition1st Edition
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Authors (2):
Bastiaan Sjardin
Bastiaan Sjardin
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Bastiaan Sjardin

Bastiaan Sjardin is a data scientist and founder with a background in artificial intelligence and mathematics. He has a MSc degree in cognitive science obtained at the University of Leiden together with on campus courses at Massachusetts Institute of Technology (MIT). In the past 5 years, he has worked on a wide range of data science and artificial intelligence projects. He is a frequent community TA at Coursera in the social network analysis course from the University of Michigan and the practical machine learning course from Johns Hopkins University. His programming languages of choice are Python and R. Currently, he is the cofounder of Quandbee (http://www.quandbee.com/), a company providing machine learning and artificial intelligence applications at scale.
Read more about Bastiaan Sjardin

Alberto Boschetti
Alberto Boschetti
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Alberto Boschetti

Alberto Boschetti is a data scientist with expertise in signal processing and statistics. He holds a Ph.D. in telecommunication engineering and currently lives and works in London. In his work projects, he faces challenges ranging from natural language processing (NLP) and behavioral analysis to machine learning and distributed processing. He is very passionate about his job and always tries to stay updated about the latest developments in data science technologies, attending meet-ups, conferences, and other events.
Read more about Alberto Boschetti

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Setting up the VM for this chapter


As machine learning needs a lot of computational power, in order to save some resources (especially memory) we will use the Spark environment not backed by YARN in this chapter. This mode of operation is named standalone and creates a Spark node without cluster functionalities; all the processing will be on the driver machine and won't be shared. Don't worry; the code that we will see in this chapter will work in a cluster environment as well.

In order to operate this way, perform the following steps:

  1. Turn on the virtual machine using the vagrant up command.

  2. Access the virtual machine when it's ready, with vagrant ssh.

  3. Launch Spark standalone mode with the IPython Notebook from inside the virtual machine with ./start_jupyter.sh.

  4. Open a browser pointing to http://localhost:8888.

To turn it off, use the Ctrl + C keys to exit the IPython Notebook and vagrant halt to turn off the virtual machine.

Note

Note that, even in this configuration, you can access the Spark...

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Large Scale Machine Learning with Python
Published in: Aug 2016Publisher: PacktISBN-13: 9781785887215

Authors (2)

author image
Bastiaan Sjardin

Bastiaan Sjardin is a data scientist and founder with a background in artificial intelligence and mathematics. He has a MSc degree in cognitive science obtained at the University of Leiden together with on campus courses at Massachusetts Institute of Technology (MIT). In the past 5 years, he has worked on a wide range of data science and artificial intelligence projects. He is a frequent community TA at Coursera in the social network analysis course from the University of Michigan and the practical machine learning course from Johns Hopkins University. His programming languages of choice are Python and R. Currently, he is the cofounder of Quandbee (http://www.quandbee.com/), a company providing machine learning and artificial intelligence applications at scale.
Read more about Bastiaan Sjardin

author image
Alberto Boschetti

Alberto Boschetti is a data scientist with expertise in signal processing and statistics. He holds a Ph.D. in telecommunication engineering and currently lives and works in London. In his work projects, he faces challenges ranging from natural language processing (NLP) and behavioral analysis to machine learning and distributed processing. He is very passionate about his job and always tries to stay updated about the latest developments in data science technologies, attending meet-ups, conferences, and other events.
Read more about Alberto Boschetti