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Spark for Machine Learning

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  • $14.00 CAD
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Proceeds of the purchase of this Spark for Machine Learning will go towards feeding a hungry ham and his family.

Looking for something to do at home? Online learning can be fun and rewarding. Beat the isolation cabin fever and get a leg up on your professional work colleagues. Position yourself better for the next promotion, or a head start on a new career. You are in full control and the sky is the limit. Now is the time to take Default Title for a spin around your cranium and enlighten the mind and not the stomach. Your bathroom scale will thank us both :)

Spark lets you apply machine learning techniques to data in real time, giving users immediate machine-learning based insights based on what's happening right now. Using Spark, we can create machine learning models and programs that are distributed and much faster compared to standard machine learning toolkits such as R or Python.

In this course, you’ll learn how to use the Spark MLlib. You’ll find out about the supervised and unsupervised ML algorithms. You’ll build classifications models, extracting proper futures from text using Word2Vect to achieve this. Next, we’ll build a Logistic Regression Model with Spark. Then we’ll find clusters and correlations in our data using K-Means clustering. We’ll learn how to validate models using cross-validation and area under the ROC measurement.

You’ll also build an effective Recommendation Model using distributed Spark algorithm. We will look at graph processing with GraphX library. By the end of the course, you’ll be able to focus on leveraging Spark to create fast and efficient machine learning programs.

About the author

Tomasz Lelek is a Software Engineer who programs mostly in Java and Scala. He is a fan of microservices architecture and functional programming. He dedicates considerable time and effort to be better every day. Recently, he’s been diving into Big Data technologies such as Apache Spark and Hadoop. He is passionate about nearly everything associated with software development.

Tomasz thinks that we should always try to consider different solutions and approaches before solving a problem. Recently, he was a speaker at several conferences in Poland - Confitura and JDD (Java Developer’s Day) and also at Krakow Scala User Group.

He also conducted a live coding session at Geecon Conference.

Who is the target audience?

  • This video course is for those who are familiar with machine learning and now want to use Spark to develop efficient and fast machine learning systems.

Spark for Machine Learning

Retail value $11.00

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