DSCI-272: Predicting with Cloudera Machine Learning
Course covers machine learning workflows and operations where participants explore, visualize, and analyze data.
Course Overview
Course covers machine learning workflows and operations where participants explore, visualize, and analyze data.
Enterprise data science teams need collaborative access to business data, tools, and computing resources required to develop and deploy machine learning workflows. Cloudera Machine Learning (CML), part of the Cloudera Data Platform (CDP), provides the solution, giving data science teams the required resources.
This course covers machine learning workflows and operations using CML. Participants explore, visualize, and analyze data. You will also train, evaluate, and deploy machine learning models.
The course walks through an end-to-end data science and machine learning workflow based on realistic scenarios and datasets from a fictitious technology company. The demonstrations and exercises are conducted in Python (with PySpark) using CML.
Course Objectives
Through lecture and hands-on exercises, you will learn how to:
Utilize Cloudera SDX and other components of the Cloudera Data Platform to locate data for machine learning experiments
Use an Applied ML Prototype (AMP)
Manage machine learning experiments
Connect to various data sources and explore data
Utilize Apache Spark and Spark ML
Deploy an ML model as a REST API
Manage and monitor deployed ML models
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