Python Deep Learning for Beginners: Theory and Practices step-by-step using TensorFlow 2.0 and Keras (Machine Learning & Data Science for Beginners) by AI Publishing
Requirements: .ePUB, .PDF, .MOBI/.AZW reader, 23 MB
Overview: Artificial intelligence is the rage today!
While you may find it difficult to understand the most recent advancements in AI, it simply boils down to two most celebrated developments: Machine Learning and Deep Learning.
In 2020, Deep Learning is leagues ahead because of its supremacy when it comes to accuracy, especially when trained with enormous amounts of data. Deep Learning, essentially, is a subset of Machine Learning, but it’s capable of achieving tremendous power and flexibility. And the era of big data technology presents vast opportunities for incredible innovations in deep learning.
How Is This Book Different?
This book gives equal importance to the theoretical as well as practical aspects of deep learning. You will understand how high-performing deep learning algorithms work. In every chapter, the theoretical explanation of the different types of deep learning techniques is followed by practical examples.
You will learn how to implement different deep learning techniques using the TensorFlow Keras library for Python. Each chapter contains exercises that you can use to assess your understanding of the concepts explained in that chapter. Also, in the Resources, the Python notebook for each chapter is provided.
Genre: Non-Fiction > Tech & Devices
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