9781492085256 - machine learning for financial risk management with python: algorithms for modeling risk de karasan, abdullah (32 resultados)
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Librería: Bay State Book Company, North Smithfield, RI, Estados Unidos de AmericaBay State Book Company
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Paperback or Softback. Condición: New. Machine Learning for Financial Risk Management with Python: Algorithms for Modeling Risk. Book.
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EUR 60,17
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Paperback. Condición: New. Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, and risk analysts will explore Python-based machine learning and deep learning models for assessing financial risk. You'll learn how…to compare results from ML models with results obtained by traditional financial risk models.Author Abdullah Karasan helps you explore the theory behind financial risk assessment before diving into the differences between traditional and ML models.Review classical time series applications and compare them with deep learning modelsExplore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learningRevisit and improve market risk models (VaR and expected shortfall) using machine learning techniquesDevelop a credit risk based on a clustering technique for risk bucketing, then apply Bayesian estimation, Markov chain, and other ML modelsCapture different aspects of liquidity with a Gaussian mixture modelUse machine learning models for fraud detectionIdentify corporate risk using the stock price crash metricExplore a synthetic data generation process to employ in financial risk.
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Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA
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Paperback. Condición: New. Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, and risk analysts will explore Python-based machine learning and deep learning models for assessing financial risk. You'll learn how…to compare results from ML models with results obtained by traditional financial risk models.Author Abdullah Karasan helps you explore the theory behind financial risk assessment before diving into the differences between traditional and ML models.Review classical time series applications and compare them with deep learning modelsExplore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learningRevisit and improve market risk models (VaR and expected shortfall) using machine learning techniquesDevelop a credit risk based on a clustering technique for risk bucketing, then apply Bayesian estimation, Markov chain, and other ML modelsCapture different aspects of liquidity with a Gaussian mixture modelUse machine learning models for fraud detectionIdentify corporate risk using the stock price crash metricExplore a synthetic data generation process to employ in financial risk.
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Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
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EUR 73,21
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Paperback. Condición: new. Paperback. Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, and risk analysts will explore Python-based machine learning and deep learning models for assessing financial risk. You'll… learn how to compare results from ML models with results obtained by traditional financial risk models.Author Abdullah Karasan helps you explore the theory behind financial risk assessment before diving into the differences between traditional and ML models.Review classical time series applications and compare them with deep learning modelsExplore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learningRevisit and improve market risk models (VaR and expected shortfall) using machine learning techniquesDevelop a credit risk based on a clustering technique for risk bucketing, then apply Bayesian estimation, Markov chain, and other ML modelsCapture different aspects of liquidity with a Gaussian mixture modelUse machine learning models for fraud detectionIdentify corporate risk using the stock price crash metricExplore a synthetic data generation process to employ in financial risk Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, and risk analysts will explore Python-based machine learning and deep learning models for assessing financial risk. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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EUR 61,76
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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EUR 56,50
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Paperback / softback. Condición: New. New copy - Usually dispatched within 4 working days.
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Condición: New. 2021. Paperback. . . . . .
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Condición: New. 2021. Paperback. . . . . . Books ship from the US and Ireland.
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Librería: Revaluation Books, Exeter, , Reino UnidoRevaluation Books
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Paperback. Condición: Brand New. 350 pages. 9.19x7.00x0.70 inches. In Stock.
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Librería: Majestic Books, Hounslow, , Reino UnidoMajestic Books
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Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de AmericaRarewaves USA United
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EUR 61,98
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Paperback. Condición: New. Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, and risk analysts will explore Python-based machine learning and deep learning models for assessing financial risk. You'll learn how…to compare results from ML models with results obtained by traditional financial risk models.Author Abdullah Karasan helps you explore the theory behind financial risk assessment before diving into the differences between traditional and ML models.Review classical time series applications and compare them with deep learning modelsExplore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learningRevisit and improve market risk models (VaR and expected shortfall) using machine learning techniquesDevelop a credit risk based on a clustering technique for risk bucketing, then apply Bayesian estimation, Markov chain, and other ML modelsCapture different aspects of liquidity with a Gaussian mixture modelUse machine learning models for fraud detectionIdentify corporate risk using the stock price crash metricExplore a synthetic data generation process to employ in financial risk.
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
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EUR 109,62
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Librería: moluna, Greven, , Alemaniamoluna
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EUR 76,06
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Condición: New. Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, and risk analysts will explore Python-based machine learning and deep learning models f.
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Librería: Buchpark, Trebbin, , AlemaniaBuchpark
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EUR 23,44
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Condición: Gut. Zustand: Gut | Seiten: 350 | Sprache: Englisch | Produktart: Bücher | "Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, risk analysts, and quantitative and algorithmic analysts will examine Pyt…hon-based machine learning and deep learning models for assessing financial risk. Building hands-on AI-based financial modeling skills, you'll learn how to replace traditional financial risk models with ML models. Author Abdullah Karasan helps you explore the theory behind financial risk modeling before diving into practical ways of employing ML models in modeling financial risk using Python"--.
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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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EUR 110,06
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Paperback. Condición: new. Paperback. Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, and risk analysts will explore Python-based machine learning and deep learning models for assessing financial risk. You'll… learn how to compare results from ML models with results obtained by traditional financial risk models.Author Abdullah Karasan helps you explore the theory behind financial risk assessment before diving into the differences between traditional and ML models.Review classical time series applications and compare them with deep learning modelsExplore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learningRevisit and improve market risk models (VaR and expected shortfall) using machine learning techniquesDevelop a credit risk based on a clustering technique for risk bucketing, then apply Bayesian estimation, Markov chain, and other ML modelsCapture different aspects of liquidity with a Gaussian mixture modelUse machine learning models for fraud detectionIdentify corporate risk using the stock price crash metricExplore a synthetic data generation process to employ in financial risk Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, and risk analysts will explore Python-based machine learning and deep learning models for assessing financial risk. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Librería: Rarewaves.com UK, London, Reino UnidoRarewaves.com UK
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EUR 67,56
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Paperback. Condición: New. Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, and risk analysts will explore Python-based machine learning and deep learning models for assessing financial risk. You'll learn how…to compare results from ML models with results obtained by traditional financial risk models.Author Abdullah Karasan helps you explore the theory behind financial risk assessment before diving into the differences between traditional and ML models.Review classical time series applications and compare them with deep learning modelsExplore volatility modeling to measure degrees of risk, using support vector regression, neural networks, and deep learningRevisit and improve market risk models (VaR and expected shortfall) using machine learning techniquesDevelop a credit risk based on a clustering technique for risk bucketing, then apply Bayesian estimation, Markov chain, and other ML modelsCapture different aspects of liquidity with a Gaussian mixture modelUse machine learning models for fraud detectionIdentify corporate risk using the stock price crash metricExplore a synthetic data generation process to employ in financial risk.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 91,07
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Taschenbuch. Condición: Neu. Neuware - 'Financial risk management is quickly evolving with the help of artificial intelligence. With this practical book, developers, programmers, engineers, financial analysts, risk analysts, and quantitative and algorithmic analysts will examine Python-based machine learning and deep learning mo…dels for assessing financial risk. Building hands-on AI-based financial modeling skills, you'll learn how to replace traditional financial risk models with ML models. Author Abdullah Karasan helps you explore the theory behind financial risk modeling before diving into practical ways of employing ML models in modeling financial risk using Python'.
