Description

Machine Learning – Apache Storm – Learn by Example

Machine Learning – Apache Storm – Learn by Example
MP4 | Video: AVC 1280×720 | Audio: AAC 44KHz 2ch | Duration: 3.5 Hours | 938 MB Genre: eLearning | Language: English

Real-world Solved Examples of Real-time Stream Processing! Storm is to real-time stream processing what Hadoop is to batch processing.

From simple data transformations to applying machine learning algorithms on the fly, Storm can do it all.
In this Apache Storm

– Learn by Example online course, you will learn how to use

How this course will help you

Storm to build applications which need you to be highly responsive to the latest data

, and react within seconds and minutes, such as finding the latest trending topics on

Twitter, or monitoring spikes in payment gateway failures. Learn to build a Storm topology,

control parallelism, use Trident to perform transformations, apply

Machine Learning algorithms on the fly, and so much more! Supplemental material included.

Machine Learning – Apache Storm is a powerful open source tool for real-time stream processing.

How this course will help you

It allows you to set up complex logic in your code, using APIs to perform arbitrary transformations

on streams of data from the Web, sensors and other devices.

This training course focuses on how you can use Storm to solve challenging real-world problems.

And it’s packed with future-proof topics that will be useful for a long time to come.

In this course, you’ll learn how to use Apache Storm for real-time stream processing.

You’ll walk through numerous examples of how to write topologies in Storm and execute them on a cluster.

How this course will help you

By the end of the course, you’ll have a full understanding of what makes this technology unique and

why it is so widely used by companies like Twitter, Yahoo! Mail and Craigslist.

Machine learning – Apache Storm is designed for real time stream processing.

It is a distributed event processor that can process massive amounts of data, and can perform any operation on the data in real time.

There are other open source technologies built around machine learning such as Hadoop, Spark, Mahout and so on.

The Apache Storm framework is the most popular open source real-time stream processing system.

It is written in Clojure and runs on top of distributed messaging systems like Kafka, RabbitMQ, and Amazon’s Kinesis.

This course will teach you how to set up a Storm cluster, with practical knowledge and hands-on projects.

How this course will help you

The combination of Storm and Spark is a powerful solution for real-time streaming data.

The obvious use case for these two technologies is building recommendation engines.

In this course you will learn how to scale your recommendation engine to multiple machines,

build fault tolerant topologies and stream results in real time to Apache Kafka and Solr.

Apache Storm is a distributed real-time computation system.

It can be used for analyzing live data streams coming from sensor data, click streams and Web forms.

Storm was originally developed at BackType but has now become an Apache top level project.