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Practical Machine Learning for Computer Vision: End-To-End Machine Learning for Images

MRP: Rs.1,800.00 You save: Rs.180.00 (10%)
Net Price: Rs.1,620.00
Price in points: 1620 points
9789391043834
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Minimum quantity for "Practical Machine Learning for Computer Vision: End-To-End Machine Learning for Images" is 1.

All Indian Reprints of O'Reilly are printed in Grayscale

This practical book shows you how to employ machine learning models to extract information from images. ML engineers and data scientists will learn how to solve a variety of image problems including classification, object detection, autoencoders, image generation, counting, and captioning with proven ML techniques. This book provides a great introduction to end-to-end deep learning: dataset creation, data pre-processing, model design, model training, evaluation, deployment, and interpretability.

Google engineers Valliappa Lakshmanan, Martin Görner, and Ryan Gillard show you how to develop accurate and explainable computer vision ML models and put them into large-scale production using robust ML architecture in a flexible and maintainable way. You'll learn how to design, train, evaluate, and predict with models written in TensorFlow or Keras.

You'll learn how to:

  • Design ML architecture for computer vision tasks
  • Select a model (such as ResNet, SqueezeNet, or EfficientNet) appropriate to your task
  • Create an end-to-end ML pipeline to train, evaluate, deploy, and explain your model
  • Pre-process images for data augmentation and to support learnability
  • Incorporate explainability and responsible AI best practices
  • Deploy image models as web services or on edge devices
  • Monitor and manage ML models

Books

Author 1:
Valliappa Lakshmanan
Author 2:
Martin Görner
Author 3:
Ryan Gillard
Binding:
Paperback
Condition Type:
New
Country Origin:
India
Edition:
First
Gift Wrap:
N
Leadtime to ship in days (default):
ships in 1-2 days
Leadtime to ship in days(if not in stock):
ships in 12-15 days
Pages:
484
Publication Date:
03/08/2021
Publisher:
Shroff/O'Reilly
Year:
2021

Dimensions

Dimensions (W x H x D):
7 x 9 x .9 inch

Table of Contents (9789391043834_toc.pdf, 184 Kb) [Download]