Catalog Search Results
Author
Pub. Date
[2018]
Language
English
Description
Build machine learning (ML) solutions for Java development. This book shows you that when designing ML apps, data is the key driver and must be considered throughout all phases of the project life cycle. "Practical Java machine learning" helps you understand the importance of data and how to organiza it for use within your ML project. You will be introduced to tools which can help you identify and manage your data including JSON, visualization,...
Author
Pub. Date
2022.
Language
English
Description
Google's TensorFlow framework sits at the heart of modern deep learning. Boasting practical features like multi-GPU support, network data visualization, and easy production pipelines using TensorFlow Extended (TFX), TensorFlow provides the most efficient path to professional AI applications. And the keras library, fully integrated into TensorFlow 2, makes it a snap to build and train even complex models for vision, language, and more. "TensorFlow...
Author
Pub. Date
[2021]
Edition
First edition.
Language
English
Description
"An introduction to machine learning and deep learning for beginners. Covers fundamental concepts before presenting classic machine learning models, neural networks, and modern convolutional neural networks. Includes hands-on Python experiments for each model"--
Author
Pub. Date
2017.
Edition
First edition.
Language
English
Description
Learn how to construct machine learning and data analysis scalable for big data using H2O software, using sample data sets and several machine-learning techniques including deep learning, random forests, unsupervised learning and ensemble learning.
Author
Pub. Date
[2022]
Edition
1st ed.
Language
English
Description
Incorporate deep learning into your development projects through hands-on coding and the latest versions of deep learning software, such as TensorFlow 2 and Keras. The materials used in this book are based on years of successful online education experience and feedback from thousands of online learners. You'll start with an introduction to AI, where you'll learn the history of neural networks and what sets deep learning apart from other varieties...
Author
Pub. Date
2019.
Edition
First edition.
Language
English
Description
Create and implement AI- and ML-based features in your Swift apps for iOS, macOS, tvOS, and watchOS. With this practical book, programmers and developers of all kinds will find a one-stop shop for AI and machine learning with Swift. You'll learn how to build features that use powerful AI software to identify images, make predictions, generate content, make recommendations, and more. AI is increasingly essential for every developer, and you don;t...
Author
Pub. Date
[2019]
Language
English
Description
Recent advances in storage, CPU, and GPU technology, coupled with the ease with which you can create virtual computing resources in the cloud, and the availability of Python libraries such as Pandas, Matplotlib, TensorFlow, and Scikit-learn, have made it possible to build and deploy machine learning (ML) systems at scale and get results in real-time. "Machine learning in the AWS Cloud" offers an introduction to the machine learning capabilities of...
Author
Pub. Date
[2019]
Edition
First edition.
Language
English
Description
Serverless computing is radically changing the way we build and deploy applications. With cloud providers running servers and managing machine resources, companies now can focus solely on the application's business logic and functionality. This hands-on book shows experienced programmers how to build and deploy scalable machine learning and deep learning models using serverless architectures with Microsoft Azure. You'll learn step-by-step how to...
59) Deep Learning with TensorFlow: Explore neural networks and build intelligent systems with Python
Author
Pub. Date
2018.
Edition
Second edition, fully revised and updated.
Language
English
Author
Pub. Date
2020.
Edition
Second edition.
Language
English
Description
Machine Learning with TensorFlow, Second Edition is a fully revised guide to building machine learning models using Python and TensorFlow. You'll apply core ML concepts to real-world challenges, such as sentiment analysis, text classification, and image recognition. Hands-on examples illustrate neural network techniques for deep speech processing, facial identification, and auto-encoding with CIFAR-10.
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