Apache Spark Machine Learning Project (House Sale Price Prediction)

Description

Apache Spark Machine Learning Project (House Sale Price Prediction) for beginners using Databricks Notebook (Unofficial) (Community edition Server) 

In this Data Science Machine Learning project, we will predict the sales prices in the Housing data set using LinearRegression one of the predictive models.

• Explore Apache Spark and Machine Learning on the Databricks platform.

• Launching Spark Cluster

• Create a Data Pipeline

• Process that data using a Machine Learning model (Spark ML Library)

• Hands-on learning

• Real time Use Case 

• Publish the Project on the Web to Impress your recruiter 

• Graphical Representation of Data using Databricks notebook.

• Transform structured data using SparkSQL and DataFrames

  
  

Predict sales prices a Real-time Use Case on Apache Spark

About Databricks: 

Databricks lets you start writing Spark ML code instantly so you can focus on your data problems.

What Will I Get ?

• In this course you will implement Spark Machine Learning Project House Sale Price Prediction in Apache Spark using Databricks Notebook (Community edition server)
• Launching Apache Spark Cluster
• Process that data using a Machine Learning model (Spark ML Library)
• Hands-on learning
• Create a Data Pipeline
• Real-time Use Case
• Publish the Project on Web to Impress your recruiter
• Graphical  Representation of Data using Databricks notebook.
• Transform structured data using SparkSQL and DataFrames

Requirements

• Apache Spark basic and Scala fundamental knowledge is required and SQL Basics
• Following 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)
• *You might see performance degradation for some features on Microsoft Edge and Internet Explorer.
• The following browsers are not supported:
• Mobile browsers.
• Beta, “preview,” or otherwise pre-release versions of desktop browsers.