Machine Learning with PySpark

via

DataCamp

Course Features

Duration

4 hours

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Teaching Type

Self Paced

Video Content

4 hours

Course Description

Spark is a powerful tool for Big Data. Spark transparently manages the allocation of compute tasks within a cluster. This allows for quick operations and lets you concentrate on the analysis, not worrying about the technical details. In this course you'll learn how to get data into Spark and then delve into the three fundamental Spark Machine Learning algorithms: Linear Regression, Logistic Regression/Classifiers, and creating pipelines. This course will also cover analysing large quantities of spam text messages as well as flight delays. This will give you the knowledge and skills to harness Spark's power for Machine Learning projects.

Course Overview

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Statistical Thinking in Python (Part 1)

Introduction to PySpark

What You Will Learn

Along the way you'll analyse a large dataset of flight delays and spam text messages

In this course you'll learn how to get data into Spark and then delve into the three fundamental Spark Machine Learning algorithms: Linear Regression, Logistic Regression/Classifiers, and creating pipelines

Learn how to make predictions with Apache Spark

Course Content

Expand all sections

Module 1: Introduction

Module 2: Classification

Module 3: Regression

Module 4: Ensembles Pipelines

Course Instructors

Andrew Collier

Data Scientist @ Exegetic Analytics

Andrew Collier is a Data Scientist, working mostly in R and Python but also dabbling in a wide range of other technologies. When not in front of a computer he spends time with his family and runs obsessively.