Machine learning neural statistical (22 résultats)

Etat : Very Good. 290 pp., paperback, very good. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.

Hardcover. Etat : Very Good. Image shows actual book for sale. Book Condition: Very Good; firm binding; contents very good. No Dust Jacket. Hard Cover Prentice Hall 1994 Mathematics Computing.

Taschenbuch. Etat : Neu. Neuware - Regression, classification, and neural networks for practical predictive systemsMachine learning is not magic-it is applied mathematics, statistics, and engineering working together to extract patterns from data.Behind every recommendation engine, fraud detector, forecasting model, and intelligent application lies a foundation of statistical reasoning and predictive modeling.'Learn from Data' is a practical, engineering-focused guide to statistical machine learning using Python and modern data science workflows.This book teaches developers and analysts how to build, evaluate, and improve machine learning systems through clear explanations, hands-on examples, and real-world problem solving.Why statistical machine learning mattersModern organizations rely on machine learning to: - predict outcomes and trends- classify and segment information- automate decision making- detect anomalies and fraud- personalize user experiences- uncover hidden patterns in dataUnderstanding the statistical foundations behind these systems is essential for building models that are reliable, interpretable, and useful.What you will learn- fundamentals of statistical learning- data preprocessing and feature engineering- regression modeling techniques- binary and multiclass classification- model evaluation and validation- bias, variance, and overfitting concepts- probability and statistical inference for ML- neural network fundamentals- optimization and gradient-based learning- building machine learning pipelines with PythonFrom raw data to predictive systemsThroughout the book, you will learn how to: - clean and prepare datasets effectively- select appropriate models for different problems- train and evaluate predictive systems- interpret model performance correctly- improve generalization and robustness- build maintainable machine learning workflowsEach chapter focuses on practical machine learning engineering principles rather than black-box shortcuts.Practical applications- business forecasting systems- fraud and anomaly detection- recommendation engines- customer behavior analysis- predictive analytics platforms- intelligent automation systemsThese examples reflect real-world machine learning engineering challenges.Who this book is for- aspiring machine learning engineers- data scientists- software developers entering AI- analysts learning predictive modeling- students studying machine learning- engineers building intelligent systemsIf you want to understand how machine learning works mathematically and practically, this book provides the roadmap.Model carefully.Learn from data.Build predictive systems with confidence. …

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New York, London und Toronto, Horwood 1994. 289 S. OPbd. Sehr gutes Exemplar.

Etat : New. Print on Demand.

Etat : New.

Etat : New.

Etat : As New. Unread book in perfect condition.

Etat : As New. Unread book in perfect condition.

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Taschenbuch. Etat : Neu. Intelligent Systems Modeling and Simulation II | Machine Learning, Neural Networks, Efficient Numerical Algorithm and Statistical Methods | Samsul Ariffin Abdul Karim | Taschenbuch | Studies in Systems, Decision and Control | xxiii | Englisch | 2023 | Springer | EAN 9783031040306 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Etat : New. In English.

Etat : New. In English.

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book develops a new system of modeling and simulations based on intelligence system. As we are directly moving from Third Industrial Revolution (IR3.0) to Fourth Industrial Revolution (IR4.0), there are many emergence techniques and algorithm that appear in many sciences and engineering branches. Nowadays, most industries are using IR4.0 in their product development as well as to refine their products. These include simulation on oil rig drilling, big data analytics on consumer analytics, fastest algorithm for large-scale numerical simulations and many more. These will save millions of dollar in the operating costs. Without any doubt, mathematics, statistics and computing are well blended to form an intelligent system for simulation and modeling. Motivated by this rapid development, in this book, a total of 41 chapters are contributed by the respective experts. The main scope of the book is to develop a new system of modeling and simulations based on machine learning, neural networks, efficient numerical algorithm and statistical methods. This book is highly suitable for postgraduate students, researchers as well as scientists that have interest in intelligent numerical modeling and simulations.…

Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book develops a new system of modeling and simulations based on intelligence system. As we are directly moving from Third Industrial Revolution (IR3.0) to Fourth Industrial Revolution (IR4.0), there are many emergence techniques and algorithm that appear in many sciences and engineering branches. Nowadays, most industries are using IR4.0 in their product development as well as to refine their products. These include simulation on oil rig drilling, big data analytics on consumer analytics, fastest algorithm for large-scale numerical simulations and many more. These will save millions of dollar in the operating costs. Without any doubt, mathematics, statistics and computing are well blended to form an intelligent system for simulation and modeling. Motivated by this rapid development, in this book, a total of 41 chapters are contributed by the respective experts. The main scope of the book is to develop a new system of modeling and simulations based on machine learning, neural networks, efficient numerical algorithm and statistical methods. This book is highly suitable for postgraduate students, researchers as well as scientists that have interest in intelligent numerical modeling and simulations.…

Paperback. Etat : Brand New. 718 pages. 9.26x6.10x1.44 inches. In Stock.

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Taschenbuch. Etat : Neu. Bayesian Brain | Psychology, Statistical model, Neural network, Bayesian probability, Machine learning, Experimental psychology, Bayesian inference, Hermann von Helmholtz, Internal model | Frederic P. Miller (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786130677657 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.…

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