Machine Learning with Apache Spark 3.0 using Scala
- Some programming experience is required and Scala fundamental knowledge is also required.
- Fundamental Spark Knowledge mandatory
Machine Learning with Apache Spark 3.0 using Scala with Examples and Project
“Big data” analysis is a hot and highly valuable skill – and this course will teach you the hottest technology in big data: Apache Spark. Employers including Amazon, eBay, NASA, Yahoo, and many more. All are using Spark to quickly extract meaning from massive data sets across a fault-tolerant Hadoop cluster. You’ll learn those same techniques, using your own Operating system right at home.
So, What are we going to cover in this course then?
Learn and master the art of Machine Learning through hands-on projects, and then execute them up to run on Databricks cloud computing services (Free Service) in this course. Well, the course is covering topics:
2) What is Spark ML
3) Types of Machine Learning
4) Steps Involved in the Machine learning program
5) Basic Statics
6) Data Sources
8) Extracting, transforming and selecting features
9) Classification and Regression
1) Will it Rain Tomorrow in Australia
2) Railway train arrival delay prediction
3) Predict the class of the Iris flower based on available attributes
4) Mall Customer Segmentation (K-means) Cluster
In order to get started with the course And to do that you’re going to have to set up your environment.
So, the first thing you’re going to need is a web browser that can be (Google Chrome or Firefox, or Safari, or Microsoft Edge (Latest version)) on Windows, Linux, and macOS desktop
This is completely Hands-on Learning with the Databricks environment.
Who this course is for:
- Apache Spark Beginners, Beginner Apache Spark Developer, Bigdata Engineers or Developers, Software Developer, Machine Learning Engineer, Data Scientist
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