Reader small image

You're reading from  Machine Learning with Spark. - Second Edition

Product typeBook
Published inApr 2017
Reading LevelIntermediate
PublisherPackt
ISBN-139781785889936
Edition2nd Edition
Languages
Right arrow
Authors (2):
Rajdeep Dua
Rajdeep Dua
author image
Rajdeep Dua

Rajdeep Dua has over 18 years experience in the cloud and big data space. He has taught Spark and big data at some of the most prestigious tech schools in India: IIIT Hyderabad, ISB, IIIT Delhi, and Pune College of Engineering. He currently leads the developer relations team at Salesforce India. He has also presented BigQuery and Google App Engine at the W3C conference in Hyderabad. He led the developer relations teams at Google, VMware, and Microsoft, and has spoken at hundreds of other conferences on the cloud. Some of the other references to his work can be seen at Your Story and on ACM digital library. His contributions to the open source community relate to Docker, Kubernetes, Android, OpenStack, and Cloud Foundry.
Read more about Rajdeep Dua

Manpreet Singh Ghotra
Manpreet Singh Ghotra
author image
Manpreet Singh Ghotra

Manpreet Singh Ghotra has more than 15 years experience in software development for both enterprise and big data software. He is currently working at Salesforce on developing a machine learning platform/APIs using open source libraries and frameworks such as Keras, Apache Spark, and TensorFlow. He has worked on various machine learning systems, including sentiment analysis, spam detection, and anomaly detection. He was part of the machine learning group at one of the largest online retailers in the world, working on transit time calculations using Apache Mahout, and the R recommendation system, again using Apache Mahout. With a master's and postgraduate degree in machine learning, he has contributed to, and worked for, the machine learning community.
Read more about Manpreet Singh Ghotra

View More author details
Right arrow

Introducing MovieStream

To better illustrate the design of our architecture, we will introduce a practical scenario. Let's assume that we have just been appointed to head the data science team of MovieStream, a fictitious Internet business that streams movies and television shows to its users.

MovieStream system is outlined in the following diagram:

MovieStream's current architecture

As we can see in the preceding diagram, currently, MovieStream's content editorial team is responsible for deciding which movies and shows are promoted and shown in various parts of the site. They are also responsible for creating the content for MovieStream's bulk marketing campaigns, which include e-mail and other direct marketing channels. Currently, MovieStream collects basic data on what titles are viewed by users on an aggregate basis and has access to some demographic data collected from users when they sign...

lock icon
The rest of the page is locked
Previous PageNext Page
You have been reading a chapter from
Machine Learning with Spark. - Second Edition
Published in: Apr 2017Publisher: PacktISBN-13: 9781785889936

Authors (2)

author image
Rajdeep Dua

Rajdeep Dua has over 18 years experience in the cloud and big data space. He has taught Spark and big data at some of the most prestigious tech schools in India: IIIT Hyderabad, ISB, IIIT Delhi, and Pune College of Engineering. He currently leads the developer relations team at Salesforce India. He has also presented BigQuery and Google App Engine at the W3C conference in Hyderabad. He led the developer relations teams at Google, VMware, and Microsoft, and has spoken at hundreds of other conferences on the cloud. Some of the other references to his work can be seen at Your Story and on ACM digital library. His contributions to the open source community relate to Docker, Kubernetes, Android, OpenStack, and Cloud Foundry.
Read more about Rajdeep Dua

author image
Manpreet Singh Ghotra

Manpreet Singh Ghotra has more than 15 years experience in software development for both enterprise and big data software. He is currently working at Salesforce on developing a machine learning platform/APIs using open source libraries and frameworks such as Keras, Apache Spark, and TensorFlow. He has worked on various machine learning systems, including sentiment analysis, spam detection, and anomaly detection. He was part of the machine learning group at one of the largest online retailers in the world, working on transit time calculations using Apache Mahout, and the R recommendation system, again using Apache Mahout. With a master's and postgraduate degree in machine learning, he has contributed to, and worked for, the machine learning community.
Read more about Manpreet Singh Ghotra