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Source channel @githubtrending · Post #15239 · Oct 21

#python#artificial_intelligence#cloud_ml#computer_systems#courseware#deep_learning#edge_machine_learning#embedded_ml#machine_learning#machine_learning_systems#mobile_ml#textbook#tinyml You can learn how to build real-world AI systems from start to finish with an open-source textbook originally from Harvard University. It teaches you not just how to train AI models but how to design scalable systems, manage data pipelines, deploy models in production, monitor them continuously, and optimize for devices like phones or IoT gadgets. This helps you become an engineer who can create efficient, reliable, and sustainable AI systems that work well in practice. The book offers hands-on labs, community support, and free online access, making it easier to gain practical skills in machine learning systems engineering. https://github.com/harvard-edge/cs249r_book

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djangoproject

@djangoproject · Post #550 · 01/15/2018, 07:05 AM

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http://www.wikipython.com/other-concepts/anatomy-of-a-class/ It seems obvious, but note that you must define a class before you use it. When you create a #class, it establishes its own namespace and all its own local variables (except global definitions) exist only inside that #namespace. They do not interact with other variables of the same name outside it. This leads us to one very important “feature” of classes that you need to know. If you use the same word to designate some specific value both inside and outside the class blueprint, the instance value will take precedence when you try to use that value. #learn

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