Lingua: Inglese
Editore: O'Reilly Media (edition 1), 2020
ISBN 10: 1492073059 ISBN 13: 9781492073055
Da: BooksRun, Philadelphia, PA, U.S.A.
Paperback. Condizione: Fair. 1. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.
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Da: GreatBookPrices, Columbia, MD, U.S.A.
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Paperback or Softback. Condizione: New. Machine Learning and Data Science Blueprints for Finance: From Building Trading Strategies to Robo-Advisors Using Python. Book.
EUR 55,08
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Aggiungi al carrelloPaperback. Condizione: New. Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You'll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP).Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You'll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples.This book covers:Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio managementSupervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategiesDimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve constructionAlgorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio managementReinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio managementNLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations.
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 54,12
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Da: PBShop.store UK, Fairford, GLOS, Regno Unito
EUR 50,86
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EUR 58,93
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Aggiungi al carrelloPaperback. Condizione: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.
Lingua: Inglese
Editore: O'Reilly Media, Sebastopol, 2020
ISBN 10: 1492073059 ISBN 13: 9781492073055
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
Paperback. Condizione: new. Paperback. Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You'll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP). Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You'll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples. This book covers: Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio managementSupervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategiesDimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve constructionAlgorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio managementReinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio managementNLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Da: Rarewaves.com USA, London, LONDO, Regno Unito
EUR 68,60
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Aggiungi al carrelloPaperback. Condizione: New. Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You'll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP).Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You'll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples.This book covers:Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio managementSupervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategiesDimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve constructionAlgorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio managementReinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio managementNLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations.
Da: medimops, Berlin, Germania
EUR 56,21
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Aggiungi al carrelloCondizione: very good. Gut/Very good: Buch bzw. Schutzumschlag mit wenigen Gebrauchsspuren an Einband, Schutzumschlag oder Seiten. / Describes a book or dust jacket that does show some signs of wear on either the binding, dust jacket or pages.
Da: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 55,61
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Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 50,85
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Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 59,39
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Condizione: NEW.
Lingua: Inglese
Editore: O'Reilly (WILEY UK) 2021-01-05, 2021
ISBN 10: 1492073059 ISBN 13: 9781492073055
Da: Chiron Media, Wallingford, Regno Unito
EUR 55,99
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EUR 63,51
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EUR 59,50
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Da: THE SAINT BOOKSTORE, Southport, Regno Unito
EUR 61,96
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Aggiungi al carrelloPaperback / softback. Condizione: New. New copy - Usually dispatched within 4 working days.
Condizione: New. 2021. Paperback. . . . . . Books ship from the US and Ireland.
Da: Revaluation Books, Exeter, Regno Unito
EUR 79,40
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Aggiungi al carrelloPaperback. Condizione: Brand New. 400 pages. 9.00x7.00x0.75 inches. In Stock.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 82,03
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Da: Majestic Books, Hounslow, Regno Unito
EUR 87,73
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Aggiungi al carrelloCondizione: New. pp. 400.
EUR 51,22
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Da: Rarewaves USA United, OSWEGO, IL, U.S.A.
EUR 56,91
Quantità: Più di 20 disponibili
Aggiungi al carrelloPaperback. Condizione: New. Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You'll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP).Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You'll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples.This book covers:Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio managementSupervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategiesDimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve constructionAlgorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio managementReinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio managementNLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations.
EUR 68,34
Quantità: 2 disponibili
Aggiungi al carrelloCondizione: New. Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry.&U.