Machine Learning with MATLAB
2022-02-23 Gaby Arellano-Bello, MathWorks, Inc.
Table of contents below.
MATLAB 2021 is available on nanoHUB as the simulation tool and includes most toolboxes, Simulink®, and Simulink-based products. It can be found at: https://nanohub.org/tools/matlab2021a
This video is part of nanoHUB's Hands-on Data Science and Machine Learning Training Series which can be found at: https://nanohub.org/groups/ml/handson...
Engineers and data scientists work with large amounts of data in a variety of formats such as sensor, image, video, telemetry, databases, and more. They use machine learning to find patterns in data and to build models that predict future outcomes based on historical data. In this session, we explore the fundamentals of machine learning using MATLAB. We introduce machine learning techniques available in MATLAB to quickly explore your data, evaluate machine learning algorithms, compare the results and apply the best technique to your problem.
Highlights:
• Training, evaluating and comparing a range of machine learning models
• Using refinement and reduction techniques to create models that best capture the predictive power of your data
• Running predictive models in parallel using multiple processors to expedite your results
• Deploying your models to production in a variety of formats
Table of Contents:
00:00 Machine Learning with MATLAB
01:22 There are different ways to use MATLAB
01:44 You have access via the nanoHUB!
01:54 MATLAB Demo on nanoHUB
03:37 Agenda
04:04 Hands-on Machine Learning fuel economy
04:41 Agenda
04:50 Artificial Intellegence
05:51 There are two ways
06:27 AI megatrend
07:03 Types of Machine Learning
08:45 Types of Machine Learning
08:57 Machine Learning Workflow
12:03 Machine Learning Workflow – Core
12:31 Agenda
12:38 Hands-on: Machine Learning fuel economy
12:48 Let's try it out
12:50 MATLAB Demo on nanoHUB
35:49 Setting up the documentation
35:55 Setting up the documentation
35:56 Agenda
35:57 Machine Learning Workflow
36:05 The broadest range of choices
36:34 Machine Learning for Edge Analytics and Code Deployment
36:37 Using MATLAB with Other Languages
36:56 Self-Paced Online Trainings
37:05 Browse self-paced onine courses
37:20 MATLAB Onramp
37:48 My Courses
37:51 Machine Learning Onramp
37:59 Self-Paced Onine Trainings
38:12 Other Resources: Similar content
38:26 Other Resources
38:43 Leverage the MATLAB Community
39:12 How do other communities share materials?
39:28 Call to action
This presentation and related downloads can be found on nanoHUB at: https://nanohub.org/resources/35940
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