Deep Learning with TensorFlow 2ed pdf+epub

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Every week, we follow news of applications and the shocking results obtained from them, thanks to the artificial intelligence algorithms applied in different fields. What we are witnessing is one of the biggest accelerations in the entire history of this sector, and the main suspect behind these important developments is called deep learning. Deep learning comprises a vast set of algorithms that are based on the concept of neural networks and expand to contain a huge number of nodes that are disseminated at several levels of depth. Though the concept of neural networks, the so-called Artificial Neural Network (ANN), dates back to the late 1940s, initially, they were difficult to be used because of the need for huge computational power resources and the lack of data required to train the algorithms. Presently, the ability to use graphics processors (GPUs) in parallel to perform intensive calculation operations has completely opened the way to the use of deep learning. In this context, we propose the second edition of this book, with expanded and revised contents that introduce the core concepts of deep learning, using the last version of TensorFlow.

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