Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Pro Deep Learning with Tensorflow 2.0: A Mathematical Approach to Advanced Artificial Intelligence in Python

Pro Deep Learning with Tensorflow 2.0: A Mathematical Approach to Advanced Artificial Intelligence in Python

Pattanayak, Santanu

Paperback

General ComputersProbability & StatisticsProgramming

Publisher Price: $64.99

ISBN10: 1484289307
ISBN13: 9781484289303
Publisher: Apress
Published: Jan 1 2023
Pages: 652
Weight: 2.53
Height: 1.35 Width: 7.00 Depth: 10.00
Language: English

This book builds upon the foundations established in its first edition, with updated chapters and the latest code implementations to bring it up to date with Tensorflow 2.0.

Pro Deep Learning with TensorFlow 2.0 begins with the mathematical and core technical foundations of deep learning. Next, you will learn about convolutional neural networks, including new convolutional methods such as dilated convolution, depth-wise separable convolution, and their implementation. You'll then gain an understanding of natural language processing in advanced network architectures such as transformers and various attention mechanisms relevant to natural language processing and neural networks in general. As you progress through the book, you'll explore unsupervised learning frameworks that reflect the current state of deep learning methods, such as autoencoders and variational autoencoders. The final chapter covers the advanced topic of generative adversarial networks and their variants, such as cycle consistency GANs and graph neural network techniques such as graph attention networks and GraphSAGE.

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