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Beginning Deep Learning with TensorFlow - (BookRAR)

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名前:Beginning Deep Learning with TensorFlow - (BookRAR)
_DESCRIPTION_:

Description

Incorporate deep learning into your development projects through hands-on coding and the latest versions of deep learning software, such as TensorFlow 2 and Keras. The materials used in this book are based on years of successful online education experience and feedback from thousands of online learners.
You’ll start with an introduction to AI, where you’ll learn the history of neural networks and what sets deep learning apart from other varieties of machine learning. Discovery the variety of deep learning frameworks and set-up a deep learning development environment. Next, you’ll jump into simple classification programs for hand-writing analysis. Once you’ve tackled the basics of deep learning, you move on to TensorFlow 2 specifically. Find out what exactly a Tensor is and how to work with MNIST datasets. Finally, you’ll get into the heavy lifting of programming neural networks  and working with a wide variety of neural network types such as GANs and RNNs.  
Deep Learning is a new area of Machine Learning research widely used in popular applications, such as voice assistant and self-driving cars. Work through the hands-on material in this book and become a TensorFlow programmer!      

What You’ll Learn

   Develop using deep learning algorithms
   Build deep learning models using TensorFlow 2
   Create classification systems and other, practical deep learning applications

Who This Book Is For

   Students, programmers, and researchers with no experience in deep learning who want to build up their basic skillsets. Experienced machine learning programmers and engineers might also find value in updating their skills.

Book Details

   Language: English
   Published: 2022
   ISBN: 148427914X
   Format: True (PDF, EPUB)
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カテゴリ:Books
言語:English  English
合計サイズ:61.20 MB
情報のハッシュ:24347CB5BB6393F10AAAA8BEADD8F92D9CCBF94F
を追加することによって:bookrar Verified UploaderBook Worm
追加日:2022-01-29 22:58:26
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