https://github.com/rishisankineni/machine-learning-pipeline-lr-pyspark

Power Plant ML Pipeline Application - Apache Spark
https://github.com/rishisankineni/machine-learning-pipeline-lr-pyspark

apache-spark edx-course pyspark

Last synced: about 1 month ago
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Power Plant ML Pipeline Application - Apache Spark

• Host: GitHub
• URL: https://github.com/rishisankineni/machine-learning-pipeline-lr-pyspark
• Owner: RishiSankineni
• Created: 2016-10-09T19:33:48.000Z (about 8 years ago)
• Default Branch: master
• Last Pushed: 2016-12-12T01:06:26.000Z (about 8 years ago)
• Last Synced: 2024-06-24T23:28:35.695Z (6 months ago)
• Topics: apache-spark, edx-course, pyspark
• Language: Jupyter Notebook
• Homepage:
• Size: 43 KB
• Stars: 12
• Watchers: 4
• Forks: 7
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# MLPipeline-Lab1-EdX

#![Spark Logo](http://spark-mooc.github.io/web-assets/images/ta_Spark-logo-small.png) + ![Python Logo](http://spark-mooc.github.io/web-assets/images/python-logo-master-v3-TM-flattened_small.png)

Power Plant Machine Learning Pipeline Application -EdX - Lab1- Big Data Analysis with Apache Spark

This notebook is an end-to-end exercise of performing Extract-Transform-Load and Exploratory Data Analysis on a real-world dataset, and then applying several different machine learning algorithms to solve a supervised regression problem on the dataset.

** This notebook covers: **

* *Part 1: Business Understanding*

* *Part 2: Load Your Data*

* *Part 3: Explore Your Data*

* *Part 4: Visualize Your Data*

* *Part 5: Data Preparation*

* *Part 6: Data Modeling*

* *Part 7: Tuning and Evaluation*

*Our goal is to accurately predict power output given a set of environmental readings from various sensors in a natural gas-fired power generation plant.*