Building Machine Learning Model using Apache Spark | PySpark MLlib Tutorial

Welcome to the world of data-driven insights! In this video, we dive into the fascinating realm of machine learning and explore how to build powerful models using Apache Spark. Join us as we embark on a journey of harnessing the capabilities of Apache Spark, a robust distributed computing framework, to tackle complex data challenges and unlock the potential of machine learning algorithms. Discover the step-by-step process of data preprocessing, feature engineering, model training, and evaluation using Apache Spark's scalable and efficient tools. Whether you're a data enthusiast or a budding data scientist, this tutorial equips you with the knowledge and skills to leverage Apache Spark's immense power and create accurate and efficient machine learning models. Get ready to elevate your data analysis game and unlock the true potential of machine learning with Apache Spark!

Code for this lecture: https://github.com/ashaypatil11/spark...

Data file used in the lecture: https://github.com/ashaypatil11/spark...

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Anaconda Distributions Installation link:
https://www.anaconda.com/products/dis...

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Apache Spark Installation links:

1. Download JDK: https://www.oracle.com/in/java/techno...

2. Download Python: https://www.python.org/downloads/

3. Download Spark: https://spark.apache.org/downloads.html
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Audience

This tutorial has been prepared for professionals/students aspiring to learn deep knowledge of Big Data Analytics using Apache Spark and become a Spark Developer and Data Engineer roles. In addition, it would be useful for Analytics Professionals and ETL developers as well.

Prerequisites

Before proceeding with this full course, it is good to have prior exposure to Python programming, database concepts, and any of the Linux operating system flavors.

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