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Building Big Data Pipelines with PySpark + MongoDB + Bokeh

Building Big Data Pipelines with PySpark + MongoDB + Bokeh
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Link : Building Big Data Pipelines with PySpark + MongoDB + Bokeh
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by Edwin Bomela

What you'll learn

  • PySpark Programming
  • Data Analysis
  • Python and Bokeh
  • Data Transformation and Manipulation
  • Data Visualization
  • Big Data Machine Learning
  • Geo Mapping
  • Geospatial Machine Learning
  • Creating Dashboards

Description
Welcome to the ​Building Big Data Pipelines with PySpark & MongoDB & Bokeh​ course. In

this course we will be building an intelligent data pipeline using big data technologies like

Apache Spark and MongoDB.

We will be building an ETLP pipeline, ETLP stands for Extract Transform Load and Predict.

These are the different stages of the data pipeline that our data has to go through in order for it

to become useful at the end. Once the data has gone through this pipeline we will be able to

use it for building reports and dashboards for data analysis.

The data pipeline that we will build will comprise of data processing using PySpark, Predictive

modelling using Spark’s MLlib machine learning library, and data analysis using MongoDB and

Bokeh.

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