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Release 2017b Highlights

R2017b includes new releases of MATLAB^®and Simulink^® as well as updates and bug fixes to all other products.

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See how to use MATLAB, a simple webcam, and a deep neural network to identify objects in your surroundings. This demo uses AlexNet, a pretrained deep convolutional neural network that has been trained on over a million images.

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In this webinar you will learn how to get started using machine learning tools to detect patterns and build predictive models from your datasets. In this session, you will learn about several machine learning techniques available in MATLAB and how to

Machine Learning Made Easy

Discover common uses of Kalman filters by walking through some examples. A Kalman filter is an optimal estimation algorithm used to estimate states of a system from indirect and uncertain measurements.

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Learn how to make joint use of the signal processing and machine learning techniques available in MATLAB to develop data analytics for time series and sensor processing systems

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Share your work by publishing MATLAB code from the MATLAB Editor to HTML and other formats.

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Write a basic MATLAB Program using Live Scripts and learn the concepts of indexing, if-else statements, and loops.

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Access tools such as the command history workspace browser and variable editor, save and load your workspace data, and manage windows and desktop layout.

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Learn how machine learning tools in MATLAB(R) can be used to solve regression, clustering, and classification problems.

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The abundance of cameras has created overwhelming amounts of image and video data, and the demand for image processing has only increased in order to decipher and understand the data.

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Learn about the differences between deep learning and machine learning in this MATLAB Tech Talk. Walk through several examples, and learn about how decide which method to use.

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Package MATLAB programs as standalone applications using MATLAB Compiler. Share these applications royalty-free with users who do not have MATLAB.

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