Key Features
- Learn how to implement advanced techniques in deep learning with Google’s brainchild, TensorFlow
- Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide
- Real-world contextualization of deep learning research and application
Book Description
Deep learning is the step that comes after machine learning – it is machine learning but with a more advanced implementation. Machine learning is not just for acamademics anymore. It is fast becoming a mainstream practice and deep learning has taken a front seat. With deep learning being used by many data scientists, deeper neural networks are evaluated for accurate results. Data scientists want to explore data abstraction layers and this book will be your guide on this journey. This book evaluates common, and not so common, deep neural networks and shows how these can be exploited in the real world with complex raw data using TensorFlow.
The book will give you a rundown on the current machine learning landscape, then delve into TensorFlow and how to use it by considering various data sets and use cases. Throughout the chapters, you’ll learn how to implement deep learning algorithms for your machine learning systems and integrate them into your product offerings including: search, image recognition, and language processing. Additionally, you’ll learn how to access algorithm performance and how to optimize their performance within various parameters. This can be done by comparing the algorithms against benchmarks along with teaching machines to learn from the information and determine the ideal behavior within a specific context.
After finishing the book you will be familiar with machine learning techniques, in particular TensorFlow for deep learning, and will be ready to apply your knowledge to a real research or commercial project.
What you will learn
- An overview of the machine learning landscape
- The historical development and progress of deep learning
- The theory behind and use of TensorFlow
- Access public datasets and use TensorFlow to load, process, clean, and transform data
- Use TensorFlow on real-world data sets including images and text
- Get familiar with TensorFlow by applying it in various hands-on exercises using the command line
- How to evaluate the performance of your deep learning models
- Quickly teach machines to learn from data by exploring reinforcement learning techniques
- Understand how this technology is being used in the real world by exploring active areas of deep learning research and application
About the Author
Giancarlo Zaccone has more than 10 years of experience in managing research projects, both in the scientific and industrial domains. He worked as a researcher at the National Research Council of Italy (CNR), where he was involved in a few parallel numerical computing and scientific visualization projects. Currently, he is a system and software engineer in an IT company, developing applications for space and defense domains.
Giancarlo holds a master’s degree in Physics and a postgraduate specialization in scientific computing.
You can connect with him at https://it.linkedin.com/in/giancarlozaccone.
