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Build Deeper: The Path to Deep Learning
| AUTHOR | Amaratunga, Thimira |
| PUBLISHER | Independently Published (01/09/2019) |
| PRODUCT TYPE | Paperback (Paperback) |
Description
New 2019 Edition
Build Deeper is a complete and practical guide that can help you take the first few steps in deep learning. It will guide you step-by-step, from understanding the basic concepts, to building your first practical application.
It covers:
- What Deep Learning is, and where it fits with Artificial Intelligence and Machine Learning.
- How Deep Learning came to be, its predecessors, and the path it took to evolve into what it is today.
- The important milestones it has passed through the years, and the impact they had on the field.
- What tools are available for us to learn and build deep learning applications, and how to set them up: Python, TensorFlow, Theano, Keras, and more, on any OS of your choosing: Windows, Linux, or Mac OS.
- Building our first simple deep learning model.
- The internal workings of a deep learning model.
- Using more advanced topics such as Data Augmentation, Transfer Learning, Bottleneck Features, and Fine Tuning to build a practical deep learning application.
- Getting started with Computer Vision.
All you need now is a little enthusiasm ... who knows where it will take you
Go a little deeper to discover ...
Show More
Product Format
Product Details
ISBN-13:
9781793223012
ISBN-10:
1793223017
Binding:
Paperback or Softback (Trade Paperback (Us))
Content Language:
English
More Product Details
Page Count:
272
Carton Quantity:
14
Product Dimensions:
7.00 x 0.57 x 10.00 inches
Weight:
1.05 pound(s)
Country of Origin:
US
Subject Information
BISAC Categories
Computers | Intelligence (AI) & Semantics
Descriptions, Reviews, Etc.
publisher marketing
New 2019 Edition
Build Deeper is a complete and practical guide that can help you take the first few steps in deep learning. It will guide you step-by-step, from understanding the basic concepts, to building your first practical application.
It covers:
- What Deep Learning is, and where it fits with Artificial Intelligence and Machine Learning.
- How Deep Learning came to be, its predecessors, and the path it took to evolve into what it is today.
- The important milestones it has passed through the years, and the impact they had on the field.
- What tools are available for us to learn and build deep learning applications, and how to set them up: Python, TensorFlow, Theano, Keras, and more, on any OS of your choosing: Windows, Linux, or Mac OS.
- Building our first simple deep learning model.
- The internal workings of a deep learning model.
- Using more advanced topics such as Data Augmentation, Transfer Learning, Bottleneck Features, and Fine Tuning to build a practical deep learning application.
- Getting started with Computer Vision.
All you need now is a little enthusiasm ... who knows where it will take you
Go a little deeper to discover ...
Show More
