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Apache Spark Machine Learning Project (House Sale Price Prediction)

Created by Bigdata Engineer, Last Updated 20-Feb-2021, Language:English

Apache Spark Machine Learning Project (House Sale Price Prediction)

Apache Spark Machine Learning Project (House Sale Price Prediction) for beginner using Databricks Notebook (Unofficial)

Created by Bigdata Engineer, Last Updated 20-Feb-2021, Language:English

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.

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.

Course Content

Bigdata Engineer

I am Solution Architect with 12+ year’s of experience in Banking, Telecommunication and Financial Services industry across a diverse range of roles in Credit Card, Payments, Data Warehouse and Data Center programmes

My role as Bigdata and Cloud Architect to work as part of Bigdata team to provide Software Solution.

Responsibilities includes,

- Support all Hadoop related issues
- Benchmark existing systems, Analyse existing system challenges/bottlenecks and Propose right solutions to eliminate them based on various Big Data technologies
- Analyse and Define pros and cons of various technologies and platforms
- Define use cases, solutions and recommendations
- Define Big Data strategy
- Perform detailed analysis of business problems and technical environments
- Define pragmatic Big Data solution based on customer requirements analysis
- Define pragmatic Big Data Cluster recommendations
- Educate customers on various Big Data technologies to help them understand pros and cons of Big Data
- Data Governance
- Build Tools to improve developer productivity and implement standard practices

I am sure the knowledge in these courses can give you extra power to win in life.

All the best!!