Build Spark Machine – Learning and Analytics (5 Projects)

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Exploring the Essential Features of “Build Spark Machine – Learning and Analytics (5 Projects)“

What you’ll learn:

• Build Apache Spark Machine Learning and Analytics Projects (Total 5 Projects)
• Explore Apache Spark and Machine Learning on the Databricks platform.
• Launching Spark Cluster
• Create a Data Pipeline
• Process data using a Machine Learning model (Spark ML Library)
• Hands-on learning
• Real-time Use Case
• Publish the Project on Web to Impress your recruiter

Requirements:

• Apache Spark basic and Scala fundamental knowledge is required, along with SQL Basics and Machine Learning.
• Supported browsers on Windows, Linux, or macOS desktop: Google Chrome (Latest version), Firefox (Latest version), Safari (Latest version), Microsoft Edge* (Latest version), Internet Explorer 11* on Windows 7, 8, or 10 (with latest Windows updates applied).
• Not supported browsers: Mobile browsers, Beta, “preview,” or otherwise pre-release versions of desktop browsers.

Description:

Build Apache Spark Machine Learning and Analytics Projects (Total 5 Projects) on Databricks Environment, designed for Big Data Engineers. Learn the latest Big Data Technology Tool – Apache Superset! One of the most valuable technology skills is the ability to analyze huge data sets, and this course specifically focuses on Apache Superset.

Master Machine Learning Project Building with Apache Spark:

1. eCommerce Customer Revenue Prediction Project:
   • Predict future spending of customers for an eCommerce company.
   • Use Apache Spark Machine Learning Models, specifically Linear Regression.
   • Real-time use case on the Databricks platform.
   • Create a data pipeline and publish the project on the web.
2. Predicting Customer Response to Bank Direct Telemarketing Campaign Project:
   • Analyze direct marketing campaigns of a banking institution.
   • Use Apache Spark Machine Learning Models, particularly Logistic Regression.
   • Real-time use case on the Databricks platform.
   • Create a data pipeline and publish the project on the web.
3. Prediction of Online Shoppers’ Purchasing Intention Project:
   • Real-time prediction of online shoppers’ purchasing intention.
   • Use Apache Spark Machine Learning Models, focusing on Logistic Regression.
   • Ongoing use case on the Databricks platform.
   • Distribute the project on the web to impress employers.
4. Apache Web Server Logs Analytics:
   • Analyze data (Apache Web Server log) in Apache Spark using Databricks Notebook.
   • Real-world example of Apache Web Server logs analytics.
   • Graphical representation of data using Databricks notebook.
   • Transform structured data using SparkSQL and DataFrames.
   • Launching Spark Cluster and hands-on learning.
   • Real-time use case and publishing the project on the web.
5. Predictive Analytics with Apache Spark:
   • Learn the basics of the exponential family of predict modeling.
   • Understand the different components of this family and their relationship.
   • Avoid sample bias in predictive modeling projects.
   • Classification and Regression Models using Databricks Notebook.
   • Real-time use case and publishing the project on the web.

About Databricks:

Databricks lets you start writing Spark ML code instantly, allowing you to focus on your data problems.

Who this course is for:

Beginner Apache Spark Developers, Big Data Engineers or Developers, Software Developers, Machine Learning Engineers, Data Scientists.

Please see the full list of alternative group-buy courses available here: https://lunacourse.com/shop/