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. All the results, tested with Python programs, are demonstrated rigorously, often using geometric approaches for optimization problems and;
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. All the results, tested with Python programs, are demonstrated rigorously, often using geometric approaches for optimization problems and;
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This book provides both conceptual knowledge of quantitative finance and a hands-on approach to using Python. It begins with a description;
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. Appropriate for advanced undergraduates, graduate students, and scholars with a basic knowledge of Python Applicable to many humanities disciplines;
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in the solution of problems. The book is based on Numerical Methods in Engineering with Python, which used Python 2. This new edition;
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quantitative analysis using Python, and learn how to build algorithmic trading strategies with Zipline using various market data sources. Using Zipline;
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of the markets for listed volatility and variance derivatives * Reproduce all results and graphics with IPython/Jupyter Notebooks and Python;
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quantitative jobs in industry. No background in computer science is assumed; a learner need only have a computer with access to the Internet. Using the;
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Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts;
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students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the;
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students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the;
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This book provides an introduction to quantitative marketing with Python. The book presents a hands-on approach to using Python for real;
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This book provides an introduction to quantitative marketing with Python. The book presents a hands-on approach to using Python for real;
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Use ontologies in Python, with the Owlready2 module developed for ontology-oriented programming. You will start with an introduction and;
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who want to get started with the world of programming. We assume no knowledge of Python for this book. What You Will Learn * Use if else;
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The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it;
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performance of basic calculations with Python is then explained with reference to, for example, Kepler's laws of planetary motion and gravitational;
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will be applying quantitative methods in day-to-day managerial decision-making.This updated edition now comes packaged with an;
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generative adversarial networks with examples using the TensorFlow Python library. It also serves as a quick hands-on guide to TensorFlow programming;
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is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowledge of Python;
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is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowledge of Python;
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science has never been so easy Key Features Discover how most programmers use the main Python libraries when performing statistics with;
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demonstration with interactive and incremental examples to apply pandas to finance Who This Book Is ForIf you are interested in quantitative finance;
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uncovering its underlying mathematics and showing how to apply ML methods to real-world financial data. In this book the authorsFeatured with the;
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uncovering its underlying mathematics and showing how to apply ML methods to real-world financial data. In this book the authorsFeatured with the;
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