Financial data analytics machine par chen sam (14 résultats)

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FINANCIAL DATA ANALYTICS WITH MACHINE LEARNING OPTIMIZATION AND STATISTICS (HB 2024) (Wiley Finance)
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Vendeur : Books Puddle, New York, NY, Etats-UnisBooks Puddle
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EUR 65,92
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Etat : New. 1st edition NO-PA16APR2015-KAP.

FINANCIAL DATA ANALYTICS WITH MACHINE LEARNING OPTIMIZATION AND STATISTICS (HB 2024) (Wiley Finance)
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FINANCIAL DATA ANALYTICS WITH MACHINE LEARNING OPTIMIZATION AND STATISTICS (HB 2024) (Wiley Finance)
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Vendeur : Biblios, frankfurt am main, HESSE, AllemagneBiblios
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EUR 79,70
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Hardback. Etat : New. An essential introduction to data analytics and Machine Learning techniques in the business sector In Financial Data Analytics with Machine Learning, Optimization and Statistics, a team consisting of a distinguished applied mathematician and statistician, experienced actuarial professionals and working data… analysts delivers an expertly balanced combination of traditional financial statistics, effective machine learning tools, and mathematics. The book focuses on contemporary techniques used for data analytics in the financial sector and the insurance industry with an emphasis on mathematical understanding and statistical principles and connects them with common and practical financial problems. Each chapter is equipped with derivations and proofs-especially of key results-and includes several realistic examples which stem from common financial contexts. The computer algorithms in the book are implemented using Python and R, two of the most widely used programming languages for applied science and in academia and industry, so that readers can implement the relevant models and use the programs themselves. This book can help readers become well-equipped with the following skills: To evaluate financial and insurance data quality, and use the distilled knowledge obtained from the data after applying data analytic tools to make timely financial decisionsTo apply effective data dimension reduction tools to enhance supervised learningTo describe and select suitable data analytic tools as introduced above for a given dataset depending upon classification or regression prediction purpose The book covers the competencies tested by several professional examinations, such as the Predictive Analytics Exam offered by the Society of Actuaries, and the Institute and Faculty of Actuaries' Actuarial Statistics Exam. Besides being an indispensable resource for senior undergraduate and graduate students taking courses in financial engineering, statistics, quantitative finance, risk management, actuarial science, data science, and mathematics for AI, Financial Data Analytics with Machine Learning, Optimization and Statistics also belongs in the libraries of aspiring and practicing quantitative analysts working in commercial and investment banking.

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Etat : New. Brand new! Please provide a physical shipping address.

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- Édition originale
Vendeur : Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandeKennys Bookshop and Art Galleries Ltd.
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EUR 86,77
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Etat : New. 2024. 1st Edition. hardcover. . . . . .

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EUR 107,68
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Etat : New. 2024. 1st Edition. hardcover. . . . . . Books ship from the US and Ireland.

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Vendeur : Rarewaves.com UK, London, Royaume-UniRarewaves.com UK
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EUR 74,23
EUR 76,48 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 11 disponible(s)
Hardback. Etat : New. An essential introduction to data analytics and Machine Learning techniques in the business sector In Financial Data Analytics with Machine Learning, Optimization and Statistics, a team consisting of a distinguished applied mathematician and statistician, experienced actuarial professionals and working data… analysts delivers an expertly balanced combination of traditional financial statistics, effective machine learning tools, and mathematics. The book focuses on contemporary techniques used for data analytics in the financial sector and the insurance industry with an emphasis on mathematical understanding and statistical principles and connects them with common and practical financial problems. Each chapter is equipped with derivations and proofs-especially of key results-and includes several realistic examples which stem from common financial contexts. The computer algorithms in the book are implemented using Python and R, two of the most widely used programming languages for applied science and in academia and industry, so that readers can implement the relevant models and use the programs themselves. This book can help readers become well-equipped with the following skills: To evaluate financial and insurance data quality, and use the distilled knowledge obtained from the data after applying data analytic tools to make timely financial decisionsTo apply effective data dimension reduction tools to enhance supervised learningTo describe and select suitable data analytic tools as introduced above for a given dataset depending upon classification or regression prediction purpose The book covers the competencies tested by several professional examinations, such as the Predictive Analytics Exam offered by the Society of Actuaries, and the Institute and Faculty of Actuaries' Actuarial Statistics Exam. Besides being an indispensable resource for senior undergraduate and graduate students taking courses in financial engineering, statistics, quantitative finance, risk management, actuarial science, data science, and mathematics for AI, Financial Data Analytics with Machine Learning, Optimization and Statistics also belongs in the libraries of aspiring and practicing quantitative analysts working in commercial and investment banking.