Executive Guide to AutoML

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Keith McCormick

1:02:18

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01 - Introduction

01 - How AutoML is changing analytics teams.mp4

00:50

02 - What you should know.mp4

01:32

02 - 1. Introducing AutoML

01 - What is AutoML.mp4

01:27

02 - Understanding supervised machine learning on structured data.mp4

04:34

03 - Data engineering and ML Ops.mp4

02:56

04 - Understanding the ML lifecycle.mp4

03:59

05 - The challenge of ML problem definition.mp4

02:07

03 - 2. Stages in the ML Lifecycle

01 - Which phases have been automated most successfully.mp4

01:34

02 - The challenge of automating data understanding.mp4

02:23

03 - What AutoML can and cant do during data prep.mp4

05:38

04 - AutoMLs capabilities during the modeling phase.mp4

05:36

05 - Comparing model accuracy and business evaluation.mp4

04:27

06 - Monitoring and maintaining models.mp4

02:48

04 - 3. AutoML Options

01 - The AutoML vendor landscape.mp4

04:03

02 - Demonstrating AutoML with KNIME.mp4

10:50

03 - A metaphor for AutoML.mp4

02:00

04 - Advice for team composition.mp4

04:34

05 - Conclusion

01 - Next steps.mp4

01:00

Description

An increasing number of open-source and commercial vendors are attempting to automate machine learning, and analytics leaders need to know how this impacts data science and machine learning in their organizations. In this course, machine learning specialist, trainer, and author Keith McCormick dives into what the technology can and can't do and raises important questions about team structure and organization. Keith introduces AutoML and the machine learning (ML) lifecycle. He explains why some parts of that lifecycle—such as defining the problem—cannot be automated. Keith covers stages in the ML lifecycle, with a focus on which stages have been automated successfully and which require human support. He compares model accuracy and business evaluation, then shows you how AutoML can save you time and effort in model monitoring and maintenance. Plus, Keith goes over the wide variety of AutoML options that are available to you and offers advice for team composition.

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Machine Learning

Artificial Intelligence

Keith McCormick

Instructor's Courses

I'm an independent consultant, trainer, speaker, and author of seven books. My consulting specializes in helping analytics leaders build and manage their data science teams. My training, including 20 LinkedIn Learning courses and frequent conference workshops, has reached 1000s of individuals trying to learn statistics, machine learning, and data science. I love that I am able to train and consult. Training allows me to interact with (and learn from) 100s of clients in dozens of industries every year. It prevents me from obtaining too narrow a focus, and it keeps me current. Consulting allows me to work with a smaller number of clients in detail and in-depth, working with them on real problems of immediate concern to them. It keeps me sharp. If you've encountered me through my LinkedIn Learning courses, please consider following me here on LinkedIn. I'm not able to connect with everyone, so I connect only with clients and colleagues that I know directly. But please do follow me here because I'm quite active on LinkedIn and frequently post excerpts from the courses and other content. Follow #freefirstfridays to see when I post a link to watch a course for free. My favorite kind of consulting work involves: - working with analytics management to create effective data science teams - listening carefully to my client explain their business in detail - turning their description into a research question that can be answered with their data - coaching my client on presenting possible solutions to decision-makers - working behind the scenes to get the solution deployed Specialties: For the last several years, my emphasis has been working with analytics management to more efficiently run their teams and to nurture new hires as they expand their teams. I am skilled at explaining complex methods to new users or decision-makers and can do so at any level of technical detail. I specialize in predictive models and segmentation analysis, including classification trees, neural nets, general linear model, cluster analysis, and association rules. Books and Courses The best way to find out more about me is to check out my courses on LinkedIn Learning. They have received over 500,000 views, and each one has some free content. My books can be found on Amazon, and typically that allows you to view some free content as well. I'm very proud of all of this content (listed below in my profile), but I am still primarily an active consultant. If you need consulting help, private training, or a keynote speaker, contact me, and we can discuss.

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.