Essential Tools for Machine Learning - MATLAB Video

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Machine learning is quickly becoming a powerful tool for solving complex modeling problems across a broad range of industries. It is enabling engineers and scientists to develop models which learn from data and can be deployed as a part of packaged applications that can run efficiently on embedded systems as well as cloud infrastructure. The benefits of machine learning are being realized in applications everywhere, including predictive maintenance, health monitoring, financial portfolio forecasting, and advanced driver assistance. However, successfully applying machine learning in practice presents several challenges. It is not always clear which data is going to be the most useful for prediction, and tuning machine learning hyperparameters can consume a large amount of time.
In this webinar, you will learn how machine learning tools in MATLAB address these challenges. We will demonstrate:
Working with large out-of-memory data using the MATLAB “tall” framework
Reducing dimensionality and identifying import features using advanced feature selection techniques
Best practices for tuning hyperparameters to optimize the performance of your model
How to deploy models for use in production IT systems or embedded devices

[@mahmoudbadry2730]

Please provide a link to the demo code in this webinar. Thanks!

[@leeamraa]

next time around, I would appreciate sound to be few notches higher. Thanks.

[@MIZRAIM1984]

My question is the following: how to divide the data into the train & validation sets equlibrizing them, i.e. performing a preliminary stratification. What's the command and/or option in the menue serves for that in the case of cross-validation and holdout? Thank you very much

[@jessiestone99]

extractFeatures doesn't work as shown in the video. Did matlab modify the function recently?

[@bocckoka]

what do you think, PCA or other feature selection methods would have identified the same features as NCA?

[@lakshmi3615]

Very useful information sir. Please upload how to use MATLAB for reinforcement Learning?

[@MATLAB]

Hi Lakshmi, we have several video on our channel related to using MATLAB for reinforcement learning. You may want to check out this video: ua-cam.com/video/mji2ezCGS1c/v-deo.html or check out our Onramp tutorial www.mathworks.com/learn/tutorials/reinforcement-learning-onramp.html
Here is a link to all of our videos that are about reinforcement learning: ua-cam.com/users/matlabsearch?query=reinforcement%20learning

[@blackhead1991]

Hi
What Toolbox is required to get the "spectrum" button on the signal analyzer?
Im currently on 2016a

[@nurinathira6353]

why does my classifier does not detect my response?

[@munawarhussain7878]

Mind = Blown

[@haoluong154]

Great work. Thank you very much.

[@latzobear]

those heart sounds were so creepy :(

[@Thanhtoanofficial]

Thanks Matlab

[@sorajsahu5136]

How to know what are the toolboxes available in my matlab software? Can anyone plz tell me?

[@yl9721]

type "ver" in your command window

[@kebbailayibe4192]

Bjr comment allez vous ? J'aimerais travailler sur ce projet, si vous pouvez m'aidez avec les codes charger les données dans MATLAB et classer les sons cardiaque normales et anormales.

[@fridaynightfunkinmoni7600]

Sir please i need heelp

[@gogoodman1660]

COMPONANT

[@pengchengxi4945]

Please provide a link to the demo code in this webinar. Thanks!

[@DrDreamer]

you can find it at fileExchange of mathworks (www.mathworks.com/matlabcentral/fileexchange/). just type Heart Sound Classification in search

[@jaesonbang5710]

@@DrDreamer Thank you

[@kapilsarwat8815]

@@DrDreamer link is not working!

[@kapilsarwat8815]

@@jaesonbang5710 please share the code with us, the above link is not working