{"id":8701,"date":"2020-09-15T14:35:39","date_gmt":"2020-09-15T07:35:39","guid":{"rendered":"https:\/\/icit.kmutnb.ac.th\/main\/?p=8701"},"modified":"2020-10-30T15:51:01","modified_gmt":"2020-10-30T08:51:01","slug":"matlab-seminar-september-2020","status":"publish","type":"post","link":"\/main\/matlab-seminar-september-2020\/","title":{"rendered":"\u0e02\u0e2d\u0e40\u0e23\u0e35\u0e22\u0e19\u0e40\u0e0a\u0e34\u0e0d\u0e40\u0e02\u0e49\u0e32\u0e23\u0e48\u0e27\u0e21\u0e07\u0e32\u0e19 Ascendas MATLAB Webinar \u0e02\u0e2d\u0e07\u0e40\u0e14\u0e37\u0e2d\u0e19 \u0e01\u0e31\u0e19\u0e22\u0e32\u0e22\u0e19 2020"},"content":{"rendered":"\n
Best Regression Models “Without Writing Python\/MATLAB Codes” to (C\/C++ Web Applications)<\/div><\/div>\n\n\n\n

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The Regression Learner app<\/strong> lets you explore your data, select features, specify validation schemes, optimize hyperparameters, and assess model performance to predict your data without the need of writing any code.<\/p>\n\n\n\n

You can export regression models to the MATLAB\u00ae\u202fworkspace or generate MATLAB code to integrate models into applications.<\/p>\n\n\n\n

The app takes menial workflows and tasks like setting up the validation, picking the relevant predictors, and picking the optimal model and tuning it and makes them interactive, saving you time. Giving you full transparency and automates the workflow by generating codes automatically.<\/p>\n\n\n<\/div>\n<\/div>\n\n\n\n

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Visualizing Sensor and Prototyping ADAS\/AD Algorithms (Forward Collision Warning example)<\/div><\/div>\n\n\n\n

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More Autonomy = More Sensors = More Raw Data to Visualize and Process<\/strong><\/h2>\n\n\n\n

computers to do what comes naturally to humans and animals: learn from experience. Machine learning algorithms use computational methods to \u201clearn\u201d information directly from data without relying on a predetermined equation as a model.<\/p>\n\n\n\n

Using MATLAB, engineers and other domain experts have deployed thousands of applications for predictive maintenance, sensor analytics, finance, and communication electronics.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Mixed-Signal Design with MATLAB<\/div><\/div>\n\n\n\n

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The design and analysis of Analog\/Mixed Signal Designs have become increasingly challenging with analog impairment effects in modern semiconductor technology nodes and with the integration of complex embedded digital signal processing and control algorithms. Thus, accurate modeling and rapid system-level simulation have become extremely important to be able to verify these designs before they go into production. In this webinar, we show how MathWorks tools can be used in modeling and simulating mixed-signal algorithms in different levels of abstraction. This session will demonstrate:<\/p>\n\n\n\n