Solved end-to-end Spark MLlib Projects

Solved
end-to-end
Spark MLlib Projects

Get ready to use coding projects for solving real-world business problems

Videos

Each project comes with 2-5 hours of micro-videos explaining the solution.

Code & Dataset

Get access to 50+ solved projects with iPython notebooks and datasets.

Project Experience

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Analysing Big Data with Twitter Sentiments using Spark Streaming

In this big data spark project, we will do Twitter sentiment analysis using spark streaming on the incoming streaming data.

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Spark Project - Airline Dataset Analysis using Spark MLlib

In this Hackerday, we will go through the basis of statistics and see how Spark enables us to perform statistical operations like descriptive and inferential statistics over the very large dataset.

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Who should enroll for Spark MLlib projects ?

Data Scientists and Data analysts who want to leverage the power of spark machine learning library for analysing interesting datasets.
Big Data Developers and Engineers who would like to practice hands-on machine learning using Spark.

Key Learning’s from ProjectPro’s Apache Spark MLlib Projects

Learn to implement complex machine learning algorithms like recommendations using Spark MLlib library with simple lines of code.
Learn to use spark for a variety of analytics and machine learning tasks.
Leverage the power of Spark’s powerful machine learning API for variety of predictive analytic tasks.

What will you get when you enroll for Spark MLlib projects?

Spark Machine Learning Project Source Code: Examine and implement end-to-end real-world big data and machine learning projects on apache spark from the Banking, Finance, Retail, eCommerce, and Entertainment sector using the source code.
Recorded Demo: Watch a video explanation on how to execute these Spark Machine Learning projects for practice.
Complete Solution Kit: Get access to the big data solution design, documents, and supporting reference material, if any for every spark MLlib project use case.
Mentor Support: Get your technical questions answered with mentorship from the best industry experts for a nominal fee.
Hands-On Knowledge: Equip yourself with practical skills on Spark Machine Learning component in the spark ecosystem.