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Author
Language
English
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Description
Build highly secure and scalable machine learning platforms to support the fast-paced adoption of machine learning solutions Key Features Explore different ML tools and frameworks to solve large-scale machine learning challenges in the cloud Build an efficient data science environment for data exploration, model building, and model training Learn how to implement bias detection, privacy, and explainability in ML model development Book Description...
Author
Language
English
Formats
Description
Grokking Machine Learning presents machine learning algorithms and techniques in a way that anyone can understand. This book skips the confused academic jargon and offers clear explanations that require only basic algebra. As you go, you'll build interesting projects with Python, including models for spam detection and image recognition. You'll also pick up practical skills for cleaning and preparing data.
Author
Publisher
Packt Publishing
Pub. Date
2021.
Physical Desc
1 online resource : color illustrations
Language
English
Description
Build, train, deploy, and scale deep learning models quickly and accurately, improving your productivity using the lightweight PyTorch Wrapper Key Features Become well-versed with PyTorch Lightning architecture and learn how it can be implemented in various industry domains Speed up your research using PyTorch Lightning by creating new loss functions, networks, and architectures Train and build new algorithms for massive data using distributed training...
Author
Publisher
O'Reilly Media, Inc
Pub. Date
[2022]
Edition
[First edition].
Physical Desc
1 online resource (35 pages)
Language
English
Description
Machine learning has accelerated in several industries recently, enabling companies to automate decisions and act based on predicted futures. In time, nearly all major industries will embed ML into the core of their businesses, but right now the gap between companies that successfully adopt ML and those that fail continues to grow. This report examines why so many ML initiatives stall, especially at the stage of moving models from proof of concept...
Author
Publisher
Packt
Pub. Date
[2021]
Physical Desc
1 online resource (xi, 176 pages) : illustrations
Language
English
Description
Create better and easy-to-use deep learning models with AutoKeras Key Features Design and implement your own custom machine learning models using the features of AutoKeras Learn how to use AutoKeras for techniques such as classification, regression, and sentiment analysis Get familiar with advanced concepts as multi-modal, multi-task, and search space customization Book DescriptionAutoKeras is an AutoML open-source software library that provides easy...
Author
Publisher
O'Reilly Media, Inc
Pub. Date
2020.
Edition
First edition.
Physical Desc
1 online resource (1 volume) : illustrations
Language
English
Description
Machine learning is the key to digital transformation for many businesses today. This process accelerates your company's ability to engage customers, optimize operations, empower employees, and fundamentally change and transform products. One of the best ways to get started is with Automated Machine Learning, a quick and efficient method to jumpstart your organization's use of machine learning. In this report, AI leader Wee Hyong Tok explains how...
Author
Publisher
Microsoft Press
Pub. Date
2020.
Edition
1st edition.
Physical Desc
1 online resource (400 pages)
Language
English
Description
Master machine learning concepts and develop real-world solutions Machine learning offers immense opportunities, and Introducing Machine Learning delivers practical knowledge to make the most of them. Dino and Francesco Esposito start with a quick overview of the foundations of artificial intelligence and the basic steps of any machine learning project. Next, they introduce Microsoft's powerful ML.NET library, including capabilities for data processing,...
Publisher
Scrivener Publishing
Pub. Date
2022.
Physical Desc
1 online resource.
Language
English
Description
FUNDAMENTALS AND METHODS OF MACHINE AND DEEP LEARNING The book provides a practical approach by explaining the concepts of machine learning and deep learning algorithms, evaluation of methodology advances, and algorithm demonstrations with applications. Over the past two decades, the field of machine learning and its subfield deep learning have played a main role in software applications development. Also, in recent research studies, they are regarded...
Author
Publisher
O'Reilly Media, Inc
Pub. Date
2021.
Edition
1st edition.
Physical Desc
1 online resource (65 pages)
Language
English
Description
Recent advances in machine learning have lowered the barriers to creating and using ML models. But understanding what these models are doing has only become more difficult. We discuss technological advances with little understanding of how they work and struggle to develop a comfortable intuition for new functionality. In this report, authors Austin Eovito and Marina Danilevsky from IBM focus on how to think about neural network-based language model...
Author
Publisher
Packt Publishing, Limited
Pub. Date
2022
Physical Desc
1 online resource (281 pages)
Language
English
Description
Learn how to leverage feature stores to make the most of your machine learning models Key Features Understand the significance of feature stores in the ML life cycle Discover how features can be shared, discovered, and re-used Learn to make features available for online models during inference Book Description Feature store is one of the storage layers in machine learning (ML) operations, where data scientists and ML engineers can store transformed...
Author
Publisher
Manning Publications Co
Pub. Date
[2018]
Physical Desc
1 online resource (1 volume) : illustrations
Language
English
Description
Machine Learning Systems: Designs that scale is an example-rich guide that teaches you how to implement reactive design solutions in your machine learning systems to make them as reliable as a well-built web app. About the Technology If you're building machine learning models to be used on a small scale, you don't need this book. But if you're a developer building a production-grade ML application that needs quick response times, reliability, and...
Author
Publisher
O'Reilly Media, Inc
Pub. Date
[2020]
Edition
1st edition.
Physical Desc
1 online resource
Language
English
Description
Deep learning has the reputation as an exclusive domain for math PhDs. Not so. With this book, programmers comfortable with Python will learn how to get started with deep learning right away. Using PyTorch and the fastai deep learning library, you'll learn how to train a model to accomplish a wide range of tasks-including computer vision, natural language processing, tabular data, and generative networks. At the same time, you'll dig progressively...
Publisher
Morgan Kaufmann
Pub. Date
2014
Edition
1st ed.
Physical Desc
1 online resource (1 volume) : illustrations
Language
English
Description
The conformal predictions framework is a recent development in machine learning that can associate a reliable measure of confidence with a prediction in any real-world pattern recognition application, including risk-sensitive applications such as medical diagnosis, face recognition, and financial risk prediction. Conformal Predictions for Reliable Machine Learning: Theory, Adaptations and Applications captures the basic theory of the framework, demonstrates...
Author
Publisher
dpunkt
Pub. Date
2021.
Edition
1st edition.
Physical Desc
1 online resource (432 pages)
Language
Deutsch
Description
Die Design Patterns in diesem Buch zeigen praxiserprobte Methoden und Lösungen für wiederkehrende Aufgaben beim Machine Learning. Die Autoren, drei Machine-Learning-Experten bei Google, beschreiben bewährte Herangehensweisen, um Data Scientists bei der Lösung gängiger Probleme im gesamten ML-Prozess zu unterstützen. Die Patterns bündeln die Erfahrungen von Hunderten von Experten und bieten einfache, zugängliche Best Practices. In diesem...
Author
Publisher
Packt Publishing, Limited
Pub. Date
[2022].
Physical Desc
1 online resource (xviii, 285 pages) : illustrations
Language
English
Description
Leverage top XAI frameworks to explain your machine learning models with ease and discover best practices and guidelines to build scalable explainable ML systems Key Features Explore various explainability methods for designing robust and scalable explainable ML systems Use XAI frameworks such as LIME and SHAP to make ML models explainable to solve practical problems Design user-centric explainable ML systems using guidelines provided for industrial...
Author
Publisher
O'Reilly Media
Pub. Date
2022.
Physical Desc
1 online resource
Language
English
Description
Most intermediate-level machine learning books focus on how to optimize models by increasing accuracy or decreasing prediction error. But this approach often overlooks the importance of understanding why and how your ML model makes the predictions that it does. Explainability methods provide an essential toolkit for better understanding model behavior, and this practical guide brings together best-in-class techniques for model explainability. Experienced...
Author
Publisher
O'Reilly Media, Inc
Pub. Date
2021.
Edition
1st edition.
Physical Desc
1 online resource (40 pages)
Language
English
Description
Until recently, an organization would have had to collect and store data in a central location to train a model with machine learning. Now, federated learning offers an alternative. With this report, you'll learn how to train ML models without sharing sensitive data in the process. Google software engineers Emily Glanz and Nova Fallen introduce the motivation and technologies behind federated learning, providing the context you need to integrate it...
Author
Publisher
Apress
Pub. Date
2021
Physical Desc
1 online resource (193 pages)
Language
English
Description
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 coding ideas. Using JavaScript programming...
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