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Paperback. Condition: Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
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Condition: New.
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HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Machine Learning Algorithms in Depth
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
Seller rating 5 out of 5 stars
HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Machine Learning Algorithms in Depth
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Machine Learning Algorithms in Depth
Language: English
Published by Manning Publications, 2024
ISBN 10: 1633439216 ISBN 13: 9781633439214
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Seller rating 5 out of 5 stars
Hardback. Condition: New. New copy - Usually dispatched within 4 working days.
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Machine Learning Algorithms in Depth (Hardcover)
Language: English
Published by Manning Publications, New York, 2024
ISBN 10: 1633439216 ISBN 13: 9781633439214
Hardcover. Condition: new. Hardcover. Develop a mathematical intuition around machine learning algorithms to improve model performance and effectively troubleshoot complex ML problems. For intermediate machine learning practitioners familiar with linear algebra, probability, and basic calculus. Machine Learning Algorithms in Depth dives into the design and underlying principles of some of the most exciting machine learning (ML) algorithms in the world today. With a particular emphasis on probability-based algorithms, you will learn the fundamentals of Bayesian inference and deep learning. You will also explore the core data structures and algorithmic paradigms for machine learning. You will explore practical implementations of dozens of ML algorithms, including: Monte Carlo Stock Price SimulationImage Denoising using Mean-Field Variational InferenceEM algorithm for Hidden Markov ModelsImbalanced Learning, Active Learning and Ensemble LearningBayesian Optimisation for Hyperparameter TuningDirichlet Process K-Means for Clustering ApplicationsStock Clusters based on Inverse Covariance EstimationEnergy Minimisation using Simulated AnnealingImage Search based on ResNet Convolutional Neural NetworkAnomaly Detection in Time-Series using Variational Autoencoders Each algorithm is fully explored with both math and practical implementations so you can see how they work and put into action. About the technology Fully understanding how machine learning algorithms function is essential for any serious ML engineer. This vital knowledge lets you modify algorithms to your specific needs, understand the trade-offs when picking an algorithm for a project, and better interpret and explain your results to your stakeholders. This unique guide will take you from relying on one-size-fits-all ML libraries to developing your own algorithms to solve your business needs. Machine Learning Algorithms in Depth dives into the design and underlying principles of some of the most exciting machine learning (ML) algorithms in the world today. With a particular emphasis on probability-based algorithms, you will learn the fundamentals of Bayesian inference and deep learning. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Machine Learning Algorithms in Depth
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Condition: New.
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Machine Learning Algorithms in Depth
Language: English
Published by Manning Publications 2023-08-29, 2023
ISBN 10: 1633439216 ISBN 13: 9781633439214
Paperback. Condition: New.
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Machine Learning Algorithms in Depth
Language: English
Published by Manning Publications, 2024
ISBN 10: 1633439216 ISBN 13: 9781633439214
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
First Edition
Condition: New. 2024. 1st Edition. paperback. . . . . .
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Machine Learning Algorithms in Depth
Language: English
Published by Manning Publications, US, 2024
ISBN 10: 1633439216 ISBN 13: 9781633439214
Hardback. Condition: New. Develop a mathematical intuition around machine learning algorithms to improve model performance and effectively troubleshoot complex ML problems. For intermediate machine learning practitioners familiar with linear algebra, probability, and basic calculus. Machine Learning Algorithms in Depth dives into the design and underlying principles of some of the most exciting machine learning (ML) algorithms in the world today. With a particular emphasis on probability-based algorithms, you will learn the fundamentals of Bayesian inference and deep learning. You will also explore the core data structures and algorithmic paradigms for machine learning. You will explore practical implementations of dozens of ML algorithms, including: Monte Carlo Stock Price SimulationImage Denoising using Mean-Field Variational InferenceEM algorithm for Hidden Markov ModelsImbalanced Learning, Active Learning and Ensemble LearningBayesian Optimisation for Hyperparameter TuningDirichlet Process K-Means for Clustering ApplicationsStock Clusters based on Inverse Covariance EstimationEnergy Minimisation using Simulated AnnealingImage Search based on ResNet Convolutional Neural NetworkAnomaly Detection in Time-Series using Variational Autoencoders Each algorithm is fully explored with both math and practical implementations so you can see how they work and put into action. About the technology Fully understanding how machine learning algorithms function is essential for any serious ML engineer. This vital knowledge lets you modify algorithms to your specific needs, understand the trade-offs when picking an algorithm for a project, and better interpret and explain your results to your stakeholders. This unique guide will take you from relying on one-size-fits-all ML libraries to developing your own algorithms to solve your business needs.
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Machine Learning Algorithms in Depth
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In.
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Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
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Condition: New.
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Paperback. Condition: Brand New. 325 pages. 9.25x7.37x0.81 inches. In Stock.
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Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
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Condition: New.
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paperback. Condition: New. Special order direct from the distributor.
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Machine Learning Algorithms in Depth
Language: English
Published by Manning Publications, 2024
ISBN 10: 1633439216 ISBN 13: 9781633439214
Condition: New. 2024. 1st Edition. paperback. . . . . . Books ship from the US and Ireland.
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Paperback. Condition: Brand New. 325 pages. 9.25x7.37x0.81 inches. In Stock.
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Machine Learning Algorithms in Depth
Language: English
Published by Manning Publications, US, 2024
ISBN 10: 1633439216 ISBN 13: 9781633439214
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Hardback. Condition: New. Develop a mathematical intuition around machine learning algorithms to improve model performance and effectively troubleshoot complex ML problems. For intermediate machine learning practitioners familiar with linear algebra, probability, and basic calculus. Machine Learning Algorithms in Depth dives into the design and underlying principles of some of the most exciting machine learning (ML) algorithms in the world today. With a particular emphasis on probability-based algorithms, you will learn the fundamentals of Bayesian inference and deep learning. You will also explore the core data structures and algorithmic paradigms for machine learning. You will explore practical implementations of dozens of ML algorithms, including: Monte Carlo Stock Price SimulationImage Denoising using Mean-Field Variational InferenceEM algorithm for Hidden Markov ModelsImbalanced Learning, Active Learning and Ensemble LearningBayesian Optimisation for Hyperparameter TuningDirichlet Process K-Means for Clustering ApplicationsStock Clusters based on Inverse Covariance EstimationEnergy Minimisation using Simulated AnnealingImage Search based on ResNet Convolutional Neural NetworkAnomaly Detection in Time-Series using Variational Autoencoders Each algorithm is fully explored with both math and practical implementations so you can see how they work and put into action. About the technology Fully understanding how machine learning algorithms function is essential for any serious ML engineer. This vital knowledge lets you modify algorithms to your specific needs, understand the trade-offs when picking an algorithm for a project, and better interpret and explain your results to your stakeholders. This unique guide will take you from relying on one-size-fits-all ML libraries to developing your own algorithms to solve your business needs.
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Condition: NEW.
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DIMS of security alarms and alerts: Construction concept
Language: English
Published by LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6202679328 ISBN 13: 9786202679329
Condition: New.
