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Hands-on Convolutional Neural Networks With Tensorflow

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Convolutional Neural Networks (CNN) are one of the most popular architectures used in computer vision apps. This book is an introduction to CNNs through solving real-world problems in deep learning while teaching you their implementation in popular Python library - TensorFlow. By the end of the book, you will be training CNNs in no time!

We start with an overview of popular machine learning and deep learning models, and then get you set up with a TensorFlow development environment. This environment is the basis for implementing and training deep learning models in later chapters. Then, you will use Convolutional Neural Networks to work on problems such as image classification, object detection, and semantic segmentation.

After that, you will use transfer learning to see how these models can solve other deep learning problems. You will also get a taste of implementing generative models such as autoencoders and generative adversarial networks.

Later on, you will see useful tips on machine learning best practices and troubleshooting. Finally, you will learn how to apply your models on large datasets of millions of images.

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Ketersediaan

Informasi Detail

Judul Seri

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No. Panggil

004 IFF c

Penerbit

Birmingham, UK : Packt Publishing., 2018

Deskripsi Fisik

vi + 259 hlm; 23 cm

Bahasa

English

ISBN/ISSN

9781789130331

Klasifikasi

004

Tipe Isi

text

Tipe Media

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Tipe Pembawa

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Edisi

Ed. 1

Subjek

Komputer

Info Detail Spesifik

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Pernyataan Tanggungjawab

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Versi lain/terkait

Lampiran Berkas

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