Description
Course info
Level
Beginner
Updated
Jul 20, 2021
Duration
1h 23m
Description

Design patterns capture best practices and solutions to common problems. In this course, Design Principles for Machine Learning Framework, you’ll learn to implement scalable data pipelines for machine learning systems. First, you’ll explore guiding principles for machine learning operations. Next, you’ll discover why you should use data pipelines to process incoming data in real-time. Finally, you'll learn how to evaluate the performance of a machine learning system. When you’re finished with this course, you’ll have the skills and knowledge of machine learning operations needed to orchestrate a scalable and powerful system.

About the author
About the author

Abdul Rehman is the founder of Pythonist.org and a Machine Learning Engineer. He has held several senior software architectures and technical management roles, and he is a regular conference speaker. Python is his weapon of choice.

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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
Hello everyone. My name is Abdul Rehman, and welcome to my course, Design Principles for Machine Learning Framework. I'm a machine learning engineer and a founder at Pythonist.org. During the first tech boom, agile systems helped organizations operationalize the product lifecycle, then DevOps further optimized the production lifecycle and introduced a new element, that of big data. With more businesses now turning to machine learning insights, we are on the cusp of another wave of operationalization, so welcome to machine learning operations. In this course, we are going to understand how to productionize the machine learning models in an automated, scalable, and optimized way. Some of the major topics that we will cover include introduction to machine learning operations, the DevOps for machine learning, designing data pipelines for scalability and optimizations using various tools and techniques where we will build an end‑to‑end automated pipeline for visual material testing. Evaluating the performance of a machine learning system will also be a part of this course. By the end of this course, you will know how to design and orchestrate a scalable and optimized machine learning system. Before beginning the course, you should be familiar with the basics of machine learning along with its prerequisites. I hope you will join me on this journey to learn machine learning operations with the Design Principles for Machine Learning Framework course, at Pluralsight.