Spark for Data Science with Python

Duration : 08:02:06

Guru : loonycorn

27 Learners

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Complete Course Description

With Spark, you have a single engine where you can explore and play with large amount of data, run machine learning algorithms and then use the same system to productionize your code.



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Using Spark and Python you can analyze and explore your data in an interactive environment with fast feedback. The course will show how to leverage the power of RDDs and Dataframes to manipulate data with ease. 



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Spark's core functionality and built-in libraries make it easy to implement complex algorithms like Recommendations with very few lines of code. We'll cover a variety of datasets and algorithms including PageRank, MapReduce and Graph datasets. 



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What Are The Requirements

The course assumes knowledge of Python. You can write Python code directly in the PySpark shell. If you already have IPython Notebook installed, we'll show you how to configure it for Spark



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For the Java section, we assume basic knowledge of Java. An IDE which supports Maven, like IntelliJ IDEA/Eclipse would be helpful



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What Am I Going To Get From This Course

Use Spark for a variety of analytics and Machine Learning tasks



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Implement complex algorithms like PageRank or Music Recommendations



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Work with a variety of datasets from Airline delays to Twitter, Web graphs, Social networks and Product Ratings



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What Is The Target Audience

Analysts who want to leverage Spark for analyzing interesting datasets



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Data Scientists who want a single engine for analyzing and modelling data as well as productionizing it.



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