Practical Machine Learning for Computer Vision 
by Valliappa Lakshmanan, Martin Görner, Ryan Gillard
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 p...
Price: $59.54 | Publisher: O'Reilly Media | Release: 2021
Quantum Machine Learning: An Applied Approach
by Santanu Ganguly
Know how to adapt quantum computing and machine learning algorithms. This book takes you on a journey into hands-on quantum machine learning (QML) through various options available in industry and research.The first three chapters offer insights into the combination of the science of quantum mechanics and the techniques of machine learning, where concepts of classical information technology meet the power o...
Price: $44.74 | Publisher: Apress | Release: 2021
AI and Machine Learning for On-Device Development 
by Laurence Moroney
AI is nothing without somewhere to run it. Now that mobile devices have become the primary computing device for most people, it's essential that mobile developers add AI to their toolbox. This insightful book is your guide to creating and running models on popular mobile platforms such as iOS and Android.Laurence Moroney, lead AI advocate at Google, offers an introduction to machine learning techniques and ...
Price: $48.49 | Publisher: O'Reilly Media | Release: 2021
by John Taylor, Wayne Taylor
Discover how to apply software engineering patterns to develop more robust firmware faster than traditional embedded development approaches. In the authors' experience, traditional embedded software projects tend towards monolithic applications that are optimized for their target hardware platforms. This leads to software that is fragile in terms of extensibility and difficult to test without fully integrat...
Price: $39.99 | Publisher: Apress | Release: 2021
Quantum Machine Learning with Python
by Santanu Pattanayak
Quickly scale up to Quantum computing and Quantum machine learning foundations and related mathematics and expose them to different use cases that can be solved through Quantum based algorithms.This book explains Quantum Computing, which leverages the Quantum mechanical properties sub-atomic particles. It also examines Quantum machine learning, which can help solve some of the most challenging problems in f...
Price: $28.98 | Publisher: Apress | Release: 2021
Beginning Machine Learning in the Browser
by Suryadevara Nagender Kumar
Apply Artificial Intelligence techniques in the browser or on resource constrained computing devices. Machine learning (ML) can be an intimidating subject until you know the essentials and for what applications it works. This book takes advantage of the intricacies of the ML processes by using a simple, flexible and portable programming language such as JavaScript to work with more approachable, fundamental...
Price: $29.04 | Publisher: Apress | Release: 2021
AI for Healthcare with Keras and Tensorflow 2.0
by Anshik Bansal
Learn how AI impacts the healthcare ecosystem through real-life case studies with TensorFlow 2.0 and other machine learning (ML) libraries.This book begins by explaining the dynamics of the healthcare market, including the role of stakeholders such as healthcare professionals, patients, and payers. Then it moves into the case studies. The case studies start with EHR data and how you can account for sub-popu...
Price: $36.74 | Publisher: Apress | Release: 2021
by KC Tung
This easy-to-use reference for TensorFlow 2 design patterns in Python will help you make informed decisions for various use cases. Author KC Tung addresses common topics and tasks in enterprise data science and machine learning practices rather than focusing on TensorFlow itself.When and why would you feed training data as using NumPy or a streaming dataset? How would you set up cross-validations in the tra...
Price: $22.01 | Publisher: O'Reilly Media | Release: 2021
by Gant Laborde
Given the demand for AI and the ubiquity of JavaScript, TensorFlow.js was inevitable. With this Google framework, seasoned AI veterans and web developers alike can help propel the future of AI-driven websites. In this guide, author Gant Laborde (Google Developer Expert in machine learningand the web) provides a hands-on end-to-end approach to TensorFlow.js fundamentals for a broad technical audience that in...
Price: $40.99 | Publisher: O'Reilly Media | Release: 2021
Graph-Powered Machine Learning
by Alessandro Negro
Graph-Powered Machine Learning teaches to use graph-based algorithms and data organization strategies to develop superior machine learning applications. You'll dive into the role of graphs in machine learning and big data platforms, and take an in-depth look at data source modeling, algorithm design, recommendations, and fraud detection. Explore end-to-end projects that illustrate architectures and help you...
Price: $49.99 | Publisher: Manning | Release: 2021