Hands-On-Deep-Learning-for-Images-with-TensorFlow

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Hands-On-Deep-Learning-for-Images-with-TensorFlow

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Hands-On Deep Learning for Images with TensorFlow, published by Packt

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# Hands-On Deep Learning for Images with TensorFlow

This is the code repository for [Hands-On Deep Learning for Images with TensorFlow](https://www.packtpub.com/big-data-and-business-intelligence/hands-deep-learning-images-tensorflow?utm_source=github&utm_medium=repository&utm_campaign=9781789538670), published by Packt.

**Build intelligent computer vision applications using TensorFlow and Keras**

## What is this book about?
TensorFlow is Google’s popular offering for machine learning and deep learning, quickly becoming a favorite tool for performing fast, efficient, and accurate deep learning tasks.

This book covers the following exciting features:

* Build machine learning models particularly focused on the MNIST digits
* Work with Docker and Keras to build an image classifier
* Understand natural language models to process text and images
* Prepare your dataset for machine learning
* Create classical, convolutional, and deep neural networks

If you feel this book is for you, get your [copy](https://www.amazon.com/dp/178953867X) today!

## Instructions and Navigations
All of the code is organized into folders. For example, Chapter02.

The code will look like the following:
```
 "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
```

**Following is what you need for this book:**

Hands-On Deep Learning for Images with TensorFlow is for you if you are an application developer, data scientist, or machine learning practitioner looking to integrate machine learning into application software and master deep learning by implementing practical projects in TensorFlow. Knowledge of Python programming and basics of deep learning are required to get the best out of this book.

With the following software and hardware list you can run all code files present in the book (Chapter 1-5).

### Software and Hardware List

| Chapter  | Software required | Hardware specifications  | OS required   |                    
| -------- | ------------------|--------------------------|-------------- | 
| 1        | Docker            | NVIDIA graphics card     | Windows/Ubuntu|
| 2        | Docker            |                          | Windows/Ubuntu|
| 3        | Docker            |                          | Windows/Ubuntu|
| 4        | Docker            |                          | Windows/Ubuntu|
| 5        | Docker            |                          | Windows/Ubuntu|

### Related products <Paste books from the Other books you may enjoy section>
* Deep Learning with TensorFlow - Second Edition [[Packt]](https://www.packtpub.com/big-data-and-business-intelligence/deep-learning-tensorflow-second-edition?utm_source=github&utm_medium=repository&utm_campaign=9781788831109) [[Amazon]](https://www.amazon.com/dp/1786469782)

* Linux Device Drivers Development [[Packt]](https://www.packtpub.com/big-data-and-business-intelligence/tensorflow-1x-deep-learning-cookbook?utm_source=github&utm_medium=repository&utm_campaign=9781788293594) [[Amazon]](https://www.amazon.com/dp/1788293592)

## Get to Know the Author
**Will Ballard** is the chief technology officer at GLG, responsible for engineering and IT. He was also responsible for the design and operation of large data centers that helped run site services for customers including Gannett, Hearst Magazines, NFL.com, NPR, The Washington Post, and Whole Foods. He has also held leadership roles in software development at NetSolve (now Cisco), NetSpend, and Works.com (now Bank of America).

### Suggestions and Feedback
[Click here](https://docs.google.com/forms/d/e/1FAIpQLSdy7dATC6QmEL81FIUuymZ0Wy9vH1jHkvpY57OiMeKGqib_Ow/viewform) if you have any feedback or suggestions.

### Download a free PDF

If you have already purchased a print or Kindle version of this book, you can get a DRM-free PDF version at no cost. Simply click on the link to claim your free PDF.
 <a href="https://packt.link/free-ebook/9781789538670">https://packt.link/free-ebook/9781789538670 </a>

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