Scalable programming with Scala and Spark (Udemy.com)
Use Scala and Spark for data analysis, machine learning and analytics
Created by: Loony Corn
Produced in 2019
What you will learn
- Use Spark for a variety of analytics and Machine Learning tasks
- Understand functional programming constructs in Scala
- Implement complex algorithms like PageRank or Music Recommendations
- Work with a variety of datasets from Airline delays to Twitter, Web graphs, Social networks and Product Ratings
- Use all the different features and libraries of Spark : RDDs, Dataframes, Spark SQL, MLlib, Spark Streaming and GraphX
- Write code in Scala REPL environments and build Scala applications with an IDE
Quality Score
Overall Score : 80 / 100
Course Description
Get your data to fly using Spark and Scalafor analytics, machine learning and data science
Lets parse that.
What's Spark?
If you are an analyst or a data scientist, you'reused to having multiple systems for working with data. SQL, Python, R, Java, etc. With Spark, you have a single engine where you can explore and play with large amounts of data, run machine learning algorithms and then use the same system to productionize your code.
Scala:
Scala is a general purposeprogramming language - like Java or C++. It's functional programming nature and the availability of a REPLenvironment make it particularly suited for a distributed computing framework like Spark.
Analytics:
Using Spark and Scala 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.
Machine Learning and Data Science:
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 includingPageRank, MapReduceand Graph datasets.
What's Covered:
Scala Programming Constructs: Classes, Traits, First Class Functions, Closures, Currying, Case Classes
Lot's of cool stuff ..
Music Recommendations using Alternating Least Squares and the Audioscrobbler datasetDataframes and Spark SQL to work with Twitter dataUsingthe PageRank algorithm with Google web graph datasetUsing Spark Streaming for stream processingWorking with graph data using theMarvel Social network dataset
.. and of course all the Spark basic and advanced features:
Resilient Distributed Datasets, Transformations (map, filter, flatMap), Actions (reduce, aggregate)Pair RDDs , reduceByKey, combineByKeyBroadcast and Accumulator variablesSpark for MapReduceThe Java API for SparkSpark SQL, Spark Streaming, MLlib and GraphXWho this course is for:
Yep! Engineers who want to use a distributed computing engine for batch or stream processing or bothYep! Analysts who want to leverage Spark for analyzing interesting datasetsYep! Data Scientists who want a single engine for analyzing and modelling data as well as productionizing it.
Instructor Details
- 4.0 Rating
61 Reviews
Loony Corn
Loonycorn is us, Janani Ravi andVitthal Srinivasan. Between us, we have studied at Stanford, been admitted to IIM Ahmedabadand have spent years working in tech, in the Bay Area, New York, Singapore and Bangalore.
Janani: 7 years at Google (New York, Singapore); Studied at Stanford; also worked at Flipkart and Microsoft
Vitthal: Also Google (Singapore) and studied at Stanford; Flipkart, Credit Suisse and INSEAD too
We think we might have hit upon a neat way of teaching complicated tech courses in a funny, practical, engaging way, which is why we are so excited to be here on Udemy!
We hope you will try our offerings, and think you'll like them :-)
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