Titlebook: Machine Learning Concepts with Python and the Jupyter Notebook Environment; Using Tensorflow 2.0 Nikita Silaparasetty Book 2020 Nikita Sila

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Introduction to Jupyter Notebook, however, is not the most recommended tool to use when it comes to massive machine learning programming. This is why we have developed applications like Jupyter Notebook, which aid in such programming requirements.

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Nikita SilaparasettyGain comfort in the Jupyter Notebooks environment, which makes programming in Python even easier.Build a basic understanding of more complex Machine Learning concepts and how TensorFlow simplifies the

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明智的人

An Overview of Machine LearningArtificial intelligence sounds pretty interesting, doesn’t it? It’s exciting to create a thinking machine that can do whatever you need it to do. And you don’t need to worry about learning something new and extravagant—all you need to do is learn to program.

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Introduction to Deep LearningMachine learning for artificial intelligence sounds pretty interesting so far, doesn’t it? When I first heard about it, I thought it was something out of a science fiction movie. It’s so amazing how things used to be experienced only in . life, and now they can be experienced in . life too!

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Machine Learning With PythonIn previous chapters, we saw what artificial intelligence is and how machine learning and deep learning techniques are used to train machines to become smart. In these next few chapters, we will learn how machines are trained to take data, process it, analyze it, and develop inferences from it.

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The Tensorflow Machine Learning LibraryTo recap what was stated in an earlier chapter, Python has a huge variety of machine learning libraries that can be implemented in a program. These libraries serve various purposes—mathematical, scientific, graphical, and so on. Depending on the nature and the need of the program we are developing, we can call these libraries into our program.