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

Name: Practical Machine Learning for Computer Vision: End-To-End Machine Learning for Images
Brand: O'Reilly Media
SKU: 9781098102364
Price: 6190.0 INR
Availability: InStock

by Valliappa Lakshmanan

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ISBN13: 9781098102364
Binding: Paperback
Subject: N/A
Publisher: O'Reilly Media
Publisher Imprint: O'Reilly Media
Publication Date: August 24, 2021
Pages: 350
Original Price: GBP 71.99
Language: English
Edition: N/A
Item Weight: 772 grams
BISAC Subject(s): Data Science / General, Artificial Intelligence / General, and Data Science / Neural Networks

About The Book

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 preprocessing, model design, model training, evaluation, deployment, and interpretability.

Google engineers Valliappa Lakshmanan, Martin GÃ¶rner, 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
Preprocess 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

About The Author

Gillard, Ryan: - Ryan Gillard is an AI engineer in Google Cloud's Professional Services organization, where he builds ML models for a wide variety of industries. He started his career as a research scientist in the hospital and healthcare industry. With degrees in neuroscience and physics, he loves working at the intersection of those disciplines exploring intelligence through mathematics.

Görner, Martin: - Martin Görner is a product manager for Keras/TensorFlow focused on improving the developer experience when using state-of-the-art models. He's passionate about science, technology, coding, algorithms, and everything in between.

Lakshmanan, Valliappa: - Valliappa (Lak) Lakshmanan is the director of analytics and AI solutions at Google Cloud, where he leads a team building cross-industry solutions to business problems. His mission is to democratize machine learning so that it can be done by anyone anywhere.

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