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  • Search: subject:"Python <Programmiersprache>"
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Year of publication
Subject
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Python <Programmiersprache> 13 Programmiersprache 6 Programming language 6 Theorie 4 Theory 4 Artificial intelligence 3 Künstliche Intelligenz 3 Simulation 3 Data Mining 2 Datenanalyse 2 Econophysics 2 Finanzmathematik 2 Soziophysik 2 Statistical method 2 Statistische Methode 2 Ökonophysik 2 Befehlsvorrat 1 Berechnung 1 Bergbau 1 Betriebliches Informationssystem 1 Bewertung 1 Bootstrap approach 1 Bootstrap-Statistik 1 Bootstrap-Verfahren 1 Business analysis 1 Business process management 1 Börsenhandel 1 Calculation 1 Capital market returns 1 Data mining 1 Decision theory 1 Deep Learning 1 Derivat 1 Derivat <Wertpapier> 1 Derivative 1 Entscheidungstheorie 1 Evaluation 1 Finanzierung 1 Gewerbe 1 Hedging 1
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Online availability
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Undetermined 7
Type of publication
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Book / Working Paper 13
Type of publication (narrower categories)
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Einführung 1 Lehrbuch 1 Textbook 1
Language
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English 13
Author
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Cunha, Carlo Requião da 2 Beazley, David M. 1 Bittmann, Felix 1 Bruce, Peter C. 1 Brugière, Pierre 1 Costa, Vera 1 Essa, Alfred 1 Ferreira, Diogo R. 1 Gedeck, Peter 1 Hilpisch, Yves 1 Kaabar, Sofien 1 Kanungo, Deepak K. 1 Mojarad, Shirin 1 Patel, Nitin R. 1 Rogel-Salazar, Jesús 1 Sarmento, Rui 1 Shmueli, Galit 1
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Published in...
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Chapman and Hall/CRC Data Mining and Knowledge Discovery Ser. 1 Developer's library 1 Springer eBook Collection / Business and Management 1 Springer texts in business and economics 1 SpringerBriefs in Information Systems 1 SpringerLink / Bücher 1 The Wiley finance series 1
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Source
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ECONIS (ZBW) 13
Showing 1 - 10 of 13
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Deep learning for finance : creating machine and deep learning models for trading in Python
Kaabar, Sofien - 2024
"Deep learning is rapidly gaining momentum in the world of finance and trading. But for many professional traders, this sophisticated field has a reputation for being complex and difficult. This hands-on guide teaches you how to develop a deep learning trading model from scratch using Python,...
Persistent link: https://www.econbiz.de/10015046786
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Probabilistic machine learning for finance and investing : a primer to the next generation of AI with python
Kanungo, Deepak K. - 2023 - First edition
"By moving away from flawed statistical methodologies, you'll move toward an intuitive view of probability as a mathematically rigorous statistical framework that quantifies uncertainty holistically and successfully. This book shows you how."
Persistent link: https://www.econbiz.de/10014518412
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Introduction to econophysics : contemporary approaches with Python simulations
Cunha, Carlo Requião da - 2022 - First edition
"Econophysics explores the parallels between physics and economics and is an exciting topic that is attracting increasing attention. However there is a lack of literature that explains the topic from a broad perspective. This book introduces advanced undergraduates and graduate students in...
Persistent link: https://www.econbiz.de/10012590643
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Introduction to econophysics : contemporary approaches with Python simulations
Cunha, Carlo Requião da - 2022 - First edition
"Econophysics explores the parallels between physics and economics and is an exciting topic that is attracting increasing attention. However there is a lack of literature that explains the topic from a broad perspective. This book introduces advanced undergraduates and graduate students in...
Persistent link: https://www.econbiz.de/10013174899
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Practical AI for business leaders, product managers, and entrepreneurs
Essa, Alfred; Mojarad, Shirin - 2022
Most economists agree that AI is a general purpose technology (GPT) like the steam engine, electricity, and the computer. AI will drive innovation in all sectors of the economy for the foreseeable future. Practical AI for Business Leaders, Product Managers, and Entrepreneurs is a technical...
Persistent link: https://www.econbiz.de/10014550437
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Bootstrapping : an integrated approach with Python and Stata
Bittmann, Felix - 2021
Bootstrapping is a conceptually simple statistical technique to increase the quality of estimates, conduct robustness checks and compute standard errors for virtually any statistic. This book provides an intelligible and compact introduction for students, scientists and practitioners. It not...
Persistent link: https://www.econbiz.de/10014550531
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Data mining for business analytics : concepts, techniques and applications in Python
Shmueli, Galit; Bruce, Peter C.; Gedeck, Peter; Patel, … - 2020
Foreword / by Gareth James -- Foreword / by Ravi Bapna -- Preface to the Python edition -- Overview of the data mining process -- Data visualization -- Dimension reduction -- Evaluating predictive performance -- Multiple linear regression -- k-nearest neighbors (kNN) -- The naive Bayes...
Persistent link: https://www.econbiz.de/10012194136
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Quantitative portfolio management : with applications in Python
Brugière, Pierre - 2020
This self-contained book presents the main techniques of quantitative portfolio management and associated statistical methods in a very didactic and structured way, in a minimum number of pages. The concepts of investment portfolios, self-financing portfolios and absence of arbitrage...
Persistent link: https://www.econbiz.de/10012656848
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Advanced data science and analytics with Python
Rogel-Salazar, Jesús - 2020
Cover -- Half Title -- Series Page -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- 1: No Time to Lose: Time Series Analysis -- 1.1 Time Series -- 1.2 One at a Time: Some Examples -- 1.3 Bearing with Time: Pandas Series -- 1.3.1 Pandas Time Series in Action -- 1.3.2 Time...
Persistent link: https://www.econbiz.de/10012231821
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A Primer on Process Mining : Practical Skills with Python and Graphviz
Ferreira, Diogo R. - 2017
The main goal of this book is to explain the core ideas of process mining, and to demonstrate how they can be implemented using just some basic tools that are available to any computer scientist or data scientist. It describes how to analyze event logs in order to discover the behavior of...
Persistent link: https://www.econbiz.de/10012398334
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