Artificial Intelligence Foundations: Machine Learning

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Kesha Williams

1:50:56

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01 - Introduction

01 - Introduction to AI foundations Machine learning course.mp4

00:46

02 - Reviewing the course scenarios.mp4

02:39

02 - 1. Understanding Machine Learning

01 - Exploring machine learning.mp4

03:11

02 - Examining how machines learn.mp4

03:36

03 - 2. Implementing a Machine Learning Solution

01 - Breaking down the machine learning lifecycle.mp4

03:46

02 - Framing machine learning problems.mp4

04:10

03 - Identifying a pre-built model.mp4

03:52

04 - Understanding tools used to train a model.mp4

04:18

04 - 3. Preparing Data for Machine Learning

01 - Obtaining data.mp4

04:37

02 - Visualizing and understanding data.mp4

04:51

03 - Understanding feature engineering.mp4

04:56

04 - Demo Performing feature engineering.mp4

05:58

05 - 4. Training a Machine Learning Model

01 - Understanding learning algorithms and model training.mp4

04:08

02 - Exploring learning algorithms for classification.mp4

04:27

03 - Reviewing learning algorithms for regression.mp4

05:23

04 - Examining additional learning algorithms.mp4

04:25

05 - Training a custom machine learning model.mp4

05:02

06 - Demo Training a custom machine learning model.mp4

07:39

06 - 5. Evaluating Model Performance

01 - Exploring common classification metrics.mp4

04:49

02 - Understanding the confusion matrix.mp4

04:04

03 - Exploring common regression metrics.mp4

05:14

04 - Determining feature importance.mp4

04:25

05 - Combating bias.mp4

03:38

07 - 6. Operationalizing a Machine Learning Pipeline

01 - Structuring a machine learning pipeline.mp4

03:59

02 - Demo Designing and building a pipeline.mp4

05:04

08 - Conclusion

01 - Your machine learning journey.mp4

01:59

Description

Machine learning is the most exciting branch of artificial intelligence. It allows systems to learn from data by identifying patterns and making decisions with little to no human intervention. In this course, you'll navigate the machine learning lifecycle by getting hands-on practice training your first machine learning model. Join instructor Kesha Williams as she explores widely adopted machine learning methods: supervised, unsupervised, and reinforcement. There's a focus on sourcing and preparing data and selecting the best learning algorithm for your project. After training a model, learn to evaluate model performance using standard metrics. Finally, Kesha shows you how to streamline the process by building a machine learning pipeline. If you’re looking to understand the machine learning lifecycle and the steps required to build systems, check out this course.

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Machine Learning

Artificial Intelligence

Kesha Williams

Instructor's Courses

Kesha Williams is an award-winning technology leader with 26 years of experience in tech. She's passionate about hands-on building and developing the next generation of leaders. Forbes, Amazon Web Services (AWS), and Oracle have applauded her contributions to the technology community. She's recognized, by Amazon, as an AWS Machine Learning Hero, AWS Ambassador, and Alexa Champion. Her expertise in machine learning led her to the TED stage as a winner of TED's Spotlight Presentation Academy, where she trained with the TED Institute. She holds multiple AWS certifications and has leadership training from Harvard Business School. She serves on the Board of Directors for Women in Voice in her spare time. Learn more at http://www.kesha.tech

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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.