Machine Learning Tutorial: From Beginner to Advanced

Explore the fundamentals behind machine learning, focusing on unsupervised and supervised learning. You’ll learn what each approach is, and you’ll see the differences between them. In addition, you’ll explore common machine learning techniques including clustering, classification, and regression.
Advanced topics include:
- Feature engineering for transforming raw data into features that are suitable for a machine learning algorithm.
- ROC curves, for comparing and assessing machine learning results.
- Hyperparameter optimization, so you can find the best set of parameters for a machine learning algorithm.
- Embedded systems, including best practices for preparing your machine learning models to run on embedded devices.
Learn more about using MATLAB for machine learning: bit.ly/3cj8GMc
Get a machine learning MATLAB trial: bit.ly/2T5zF6p
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[@warisdenarkhel1911]

watching one day before for my phd interview, really helpful thanks.....

[@Boredguy112]

lol, howd it go

[@mystikalle]

Great and clear overview to ML, thanks 👍

[@paulbarton4395]

I don't understand computeHeartFeatures(PCG_normal, PCG_abnormal) ...Are we supposed to already know how to write a function that computes features? If yes, where do we learn that part?

[@feyzaackgoz299]

it was a great explanation thanks!

[@nickregan5368]

thanks for the video Adam. A really basic (trivial) example would be interesting for me. By way of starting somewhere, I created some simple data, Column 1: 1, 2, 3, to 200 Column 2 = 1,0,1,0 and so on. In other words an odd number input leads to a response of 1 and an even number leads to a 0 response. I import the data to the classification learner app, it recognises column 2 as the response and column 1 as the variable. I then import data, start session, select 'all' and hit train. the best model is quadratic svm but its accuracy is only 52.3%. It would be good to see a step by step video to create simple data (where the input / output relationship is obvious), import and tune to demonstrate the process at a very basic level. Obviously i want to use it for more complicated data, but want to build on a simple start.

[@alinafetcu6133]

hello, can we use MATLAB for multispectral imaging analysis?

[@Stephan905]

yes

[@Joeddytech]

How to deploy rmtrained model

[@Pedritox0953]

Very interesting !

I love matlab but too expensive so that unfortunately no body using matlab at work. so sad :'(

[@alexanderskusnov5119]

You shouldn't buy software, it's duty of your employer.

@@alexanderskusnov5119 I know. Employers don't buy anything.

[@a.morais1186]

Selcuk Caglar \o/

[@djdelta777]

Buy single Matlab only module is not too expensive

[@Narva58]

Matlab pyhton and ... good thing

[@andiosmani1608]

Thanks Elon Musk👏👏

[@mohammedkhudher9995]

Goodnight iam mohammed from iraq and iam try to creat equivalent consumption manimum strategy controller for parallel hybrid electric vehicle can any one help me in my mission please 🙏🙏🙏🙏🙏🙏🙏🙏