مقدمة درس. Intro to Machine Learning

To succeed in this course, you must be proficient at programming in Python and basic statistics This course provides an introduction to computer vision including fundamentals of image formation, camera imaging geometry, feature detection and matching, multiview geometry including stereo, motion estimation and tracking, and classification
Your browser is not supported! This course gives you both insight into the fundamentals of image formation and analysis, as well as the ability to extract information much above the pixel level See the for using Udacity

Machine learning brings together computer science and statistics to harness that predictive power.

Intro to Machine Learning
Learn how to build deep learning applications with TensorFlow
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It will teach you how to extract and identify useful features that best represent your data, a few of the most important machine learning algorithms, and how to evaluate the performance of your machine learning algorithms
That browser is not supported by OpenWHO any longer, you will not be able to use crucial functionality such as the playback of videos We will also use a tiny bit of , which you can also learn about on Udacity
The lecture videos use Matlab for occasional demonstration because the instructor is too old to change If you need a refresher on any of these topics, you can check out these courses:• Udacity is not an accredited university and we don't confer traditional degrees

This course is also a part of our Nanodegree.

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You'll also use your TensorFlow models in the real world on mobile devices, in the cloud, and in browsers
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As mentioned in the resources note below, you can use either Matlab or the open source version Octave