Paperback. Condizione: 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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HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Aggiungi al carrelloHardback. Condizione: New. New copy - Usually dispatched within 4 working days.
EUR 72,10
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Aggiungi al carrelloCondizione: new.
Lingua: Inglese
Editore: Manning Publications, New York, 2024
ISBN 10: 1633439216 ISBN 13: 9781633439214
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Hardcover. Condizione: 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.
EUR 65,55
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Lingua: Inglese
Editore: Manning Publications 2023-08-29, 2023
ISBN 10: 1633439216 ISBN 13: 9781633439214
Da: Chiron Media, Wallingford, Regno Unito
EUR 67,58
Quantità: 6 disponibili
Aggiungi al carrelloPaperback. Condizione: New.
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
Prima edizione
EUR 75,38
Quantità: 6 disponibili
Aggiungi al carrelloCondizione: New. 2024. 1st Edition. paperback. . . . . .
EUR 81,58
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Aggiungi al carrelloCondizione: New.
Hardback. Condizione: 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.
EUR 75,47
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Aggiungi al carrelloCondizione: New. In.
Condizione: 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.
Condizione: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
Condizione: New.
EUR 80,45
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Aggiungi al carrelloPaperback. Condizione: Brand New. 325 pages. 9.25x7.37x0.81 inches. In Stock.
Condizione: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
EUR 89,28
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EUR 85,81
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Aggiungi al carrellopaperback. Condizione: New. Special order direct from the distributor.
Condizione: New. 2024. 1st Edition. paperback. . . . . . Books ship from the US and Ireland.
EUR 108,18
Quantità: 1 disponibili
Aggiungi al carrelloHardback. Condizione: 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.
EUR 63,21
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Aggiungi al carrelloCondizione: NEW.
Lingua: Inglese
Editore: LAP LAMBERT Academic Publishing, 2020
ISBN 10: 6202679328 ISBN 13: 9786202679329
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New.
EUR 101,91
Quantità: 1 disponibili
Aggiungi al carrelloPaperback. Condizione: Brand New. 325 pages. 9.25x7.37x0.81 inches. In Stock.
Lingua: Spagnolo
Editore: Ediciones Nuestro Conocimiento, 2020
ISBN 10: 6202849584 ISBN 13: 9786202849586
Da: moluna, Greven, Germania
EUR 40,73
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