Sinossi
This book is an introduction to machine learning using Python programming language with applications in finance and business. Coverages include the prediction methods of logistic regression, Naïve Bayes, k-Nearest Neighbor, Support Vector Machine, Random Forest, Gradient Boosting, and various types of Neural Networks. Performance measurements and assessments of feature importance are also explained. The book also contains detailed examples of the applications with data. Python codes are explained in a step-by-step manner using Jupyter Notebook so that the readers can practise on their own.
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Machine Learning In Business Finance Using Python (World Scientific Series on Financial Data Analytics)
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MACHINE LEARNING IN BUSINESS FINANCE USING PYTHON
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Machine Learning In Business Finance Using Python (Hardcover)
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World Scientific Publishing Co Pte Ltd, Singapore, 2025
ISBN 10: 9819811236
ISBN 13: 9789819811236
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Hardcover. Condizione: new. Hardcover. This book is an introduction to machine learning using Python programming language with applications in finance and business. Coverages include the prediction methods of logistic regression, Naive Bayes, k-Nearest Neighbor, Support Vector Machine, Random Forest, Gradient Boosting, and various types of Neural Networks. Performance measurements and assessments of feature importance are also explained. The book also contains detailed examples of the applications with data. Python codes are explained in a step-by-step manner using Jupyter Notebook so that the readers can practise on their own. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9789819811236
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MACHINE LEARNING IN BUSINESS FINANCE USING PYTHON
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Machine Learning In Business Finance Using Python
Editore:
World Scientific Publishing Co Pte Ltd, SG, 2025
ISBN 10: 9819811236
ISBN 13: 9789819811236
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Hardback. Condizione: New. This book is an introduction to machine learning using Python programming language with applications in finance and business. Coverages include the prediction methods of logistic regression, Naïve Bayes, k-Nearest Neighbor, Support Vector Machine, Random Forest, Gradient Boosting, and various types of Neural Networks. Performance measurements and assessments of feature importance are also explained. The book also contains detailed examples of the applications with data. Python codes are explained in a step-by-step manner using Jupyter Notebook so that the readers can practise on their own. Codice articolo LU-9789819811236
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Machine Learning in Business Finance using Python: 0 (World Scientific Series On Financial Data Analytics)
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World Scientific Publishing Co Pte Ltd, 2025
ISBN 10: 9819811236
ISBN 13: 9789819811236
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MACHINE LEARNING IN BUSINESS FINANCE USING PYTHON
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Machine Learning in Business Finance using Python: 0 (World Scientific Series On Financial Data Analytics)
Editore:
World Scientific Publishing Co Pte Ltd, 2025
ISBN 10: 9819811236
ISBN 13: 9789819811236
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Da: Revaluation Books, Exeter, Regno Unito
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Hardcover. Condizione: Brand New. 270 pages. 7.50x5.98x9.02 inches. In Stock. Codice articolo x-9819811236
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Machine Learning In Business Finance Using Python (Hardcover)
Editore:
World Scientific Publishing Co Pte Ltd, Singapore, 2025
ISBN 10: 9819811236
ISBN 13: 9789819811236
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Hardcover. Condizione: new. Hardcover. This book is an introduction to machine learning using Python programming language with applications in finance and business. Coverages include the prediction methods of logistic regression, Naive Bayes, k-Nearest Neighbor, Support Vector Machine, Random Forest, Gradient Boosting, and various types of Neural Networks. Performance measurements and assessments of feature importance are also explained. The book also contains detailed examples of the applications with data. Python codes are explained in a step-by-step manner using Jupyter Notebook so that the readers can practise on their own. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9789819811236
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