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Build and deploy distributed deep learning applications on Apache Spark
Deep Learning is a subset of Machine Learning where data sets with several layers of complexity can be processed. This book teaches you the different techniques using which deep learning solutions can be implemented at scale, on Apache Spark. This will help you gain experience of implementing your deep learning models in many real-world use cases.
This book covers the following exciting features:
- Understand the basics of deep learning
- Set up Apache Spark for deep learning
- Understand the principles of distribution modeling and different types of neural networks
- Obtain an understanding of deep learning algorithms
- Discover textual analysis and deep learning with Spark
If you feel this book is for you, get your copy today!
All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
class Musician:
def __init__(self, name):
self.name = name
def __str__(self):
return f'the musician {self.name}'
def play(self):
return 'plays music'
Following is what you need for this book: If you are a Scala developer, data scientist, or data analyst who wants to learn how to use Spark for implementing efficient deep learning models, Hands-On Deep Learning with Apache Spark is for you. Knowledge of the core machine learning concepts and some exposure to Spark will be helpful.
With the following software and hardware list you can run all code files present in the book (Chapter 1-15).
| Chapter | Software required | OS required |
|---|---|---|
| 1-15 | Apache Spark, Scala, Python, Java | Windows, Mac OS X, and Linux (Any) |
We also provide a PDF file that has color images of the screenshots/diagrams used in this book. Click here to download it.
Guglielmo Iozzia is currently a big data delivery manager at Optum in Dublin. He completed his master's degree in biomedical engineering at the University of Bologna. After graduation, he joined a start-up IT company in Bologna that had implemented a new system to manage online payments. There, he worked on complex Java projects for different customers in different areas. He has also worked at the IT department of FAO, an agency of the United Nations. In 2013, he had the chance to join IBM in Dublin. There, he improved his DevOps skills, working mostly on cloud-based applications. He is a golden member, writes articles at DZone, and maintains a personal blog to share his findings and thoughts about various tech topics.
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