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Machine And Deep Learning Using Matlab Algorithms And Tools For Scientists And Engineers at Meripustak

Machine And Deep Learning Using Matlab Algorithms And Tools For Scientists And Engineers by Kamal Al-Malah, John Wiley

Books from same Author: Kamal Al-Malah

Books from same Publisher: John Wiley

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  • General Information  
    Author(s)Kamal Al-Malah
    PublisherJohn Wiley
    Edition1st Edition
    ISBN9781394209088
    Pages592
    BindingHardcover
    LanguageEnglish
    Publish YearOctober 2023

    Description

    John Wiley Machine And Deep Learning Using Matlab Algorithms And Tools For Scientists And Engineers by Kamal Al-Malah

    MACHINE AND DEEP LEARNINGIn-depth resource covering machine and deep learning methods using MATLAB tools and algorithms providing insights and algorithmic decision-making processesMachine and Deep Learning Using MATLAB introduces early career professionals to the power of MATLAB to explore machine and deep learning applications by explaining the relevant MATLAB tool or app and how it is used for a given method or a collection of methods. Its properties in terms of input and output arguments are explained the limitations or applicability is indicated via an accompanied text or a table and a complete running example is shown with all needed MATLAB command prompt code.The text also presents the results in the form of figures or tables in parallel with the given MATLAB code and the MATLAB written code can be later used as a template for trying to solve new cases or datasets. Throughout the text features worked examples in each chapter for self-study with an accompanying website providing solutions and coding samples. Highlighted notes draw the attention of the user to critical points or issues.Readers will also find information on Numeric data acquisition and analysis in the form of applying computational algorithms to predict the numeric data patterns (clustering or unsupervised learning)Relationships between predictors and response variable (supervised) categorically sub-divided into classification (discrete response) and regression (continuous response)Image acquisition and analysis in the form of applying one of neural networks and estimating net accuracy net loss and/or RMSE for the successive training validation and testing stepsRetraining and creation for image labeling object identification regression classification and text recognitionMachine and Deep Learning Using MATLAB is a useful and highly comprehensive resource on the subject for professionals advanced students and researchers who have some familiarity with MATLAB and are situated in engineering and scientific fields who wish to gain mastery over the software and its numerous applications.



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