Developers power their projects with Python because it emphasizes readability, ease of use, and access to a meticulously maintained set of packages and tools. The language itself continues to improve with every release: writing in Python is full of possibility. But to maintain a successful Python project, you need to know more than just the language. You need tooling and instincts to help you make the most out of what's available to you. Use this book as your guide to help you hone your skills and sculpt a Python project that can stand the test of time. No matter your experience level or background, Python's batteries-included standard library and rich third-party ecosystem provide a solid foundation to build your projects on. With the right intuition and background knowledge, you can take advantage of all the power Python offers. Take a guided tour of some of Python's high points to craft a project that you can sustain and build on for a long time. Run static analysis tools to detect and eliminate classes of bugs before you run code. Experiment with Python's concurrency model and develop patterns for using Python's thread and process abstractions to their full potential. Introduce yourself to Python's type hinting system: mypy. Download and run third-party Python packages and do so safely without compromising on security. Debug code using Python's built in debugger, and try procedures out in the interactive console. Run your code under new versions of the Python interpreter to unlock performance and usability improvements. All along the way, sharpen your Python instincts so you can keep your code clean and reduce the chance of bugs. Mine Python for all you can by playing to its strengths and embracing patterns that harness its potential. What You Need: The books assumes you have some experience programming in any language (not necessarily Python). To run the code presented in the book, you'll need a Python environment which you can download from https://www.python.org/downloads/.

In this textbook, basic mathematical models used in Big Data Analytics are presented and application-oriented references to relevant practical issues are made. Necessary mathematical tools are examined and applied to current problems of data analysis, such as brand loyalty, portfolio selection, credit investigation, quality control, product clustering, asset pricing etc. - mainly in an economic context. In addition, we discuss interdisciplinary applications to biology, linguistics, sociology, electrical engineering, computer science and artificial intelligence. For the models, we make use of a wide range of mathematics - from basic disciplines of numerical linear algebra, statistics and optimization to more specialized game, graph and even complexity theories. By doing so, we cover all relevant techniques commonly used in Big Data Analytics.Each chapter starts with a concrete practical problem whose primary aim is to motivate the study of a particular Big Data Analytics technique. Next, mathematical results follow - including important definitions, auxiliary statements and conclusions arising. Case-studies help to deepen the acquired knowledge by applying it in an interdisciplinary context. Exercises serve to improve understanding of the underlying theory. Complete solutions for exercises can be consulted by the interested reader at the end of the textbook; for some which have to be solved numerically, we provide descriptions of algorithms in Python code as supplementary material.This textbook has been recommended and developed for university courses in Germany, Austria and Switzerland.

Investitionsvorhaben legen den Grundstein fur die zukunftige Entwicklung eines Unternehmens und sind durch Komplexitat, Unsicherheit sowie Langfristigkeit gekennzeichnet. Das Investitionscontrolling begleitet den Investitionsprozess von Anbeginn bis zum Abschluss. Dabei kommt eine Vielzahl von Instrumenten zum Einsatz, die auf entscheidungstheoretischen Grundlagen beruhen. Angesichts des kaum zu uberblickenden Publikationsaufkommens erscheint es hilfreich, die zwischenzeitlich eher verborgenen Elemente der Entscheidungstheorie wieder sichtbar zu machen. Dies ist fur das Verstandnis und die Einordnung der Methoden ebenso unerlasslich, wie fur die korrekte Anwendung. Logische Konsequenz daraus ist, die bisher eher getrennt betrachteten Bereiche der Entscheidungstheorie und der Investitionsrechnung so zusammenzufuhren, dass Gemeinsamkeiten und Querverbindungen zwischen den einzelnen Teilgebieten offengelegt werden koennen. Das auf diese Weise entstandene Sujet ist so umfangreich, dass eine Aufteilung in zwei Bande notwendig wurde.

Investitionsvorhaben legen den Grundstein fur die zukunftige Entwicklung eines Unternehmens und sind durch Komplexitat, Unsicherheit sowie Langfristigkeit gekennzeichnet. Das Investitionscontrolling begleitet den Investitionsprozess von Anbeginn bis zum Abschluss.Dabei kommt eine Vielzahl von Instrumenten zum Einsatz, die auf entscheidungstheoretischen Grundlagen beruhen. Angesichts des kaum zu uberblickenden Publikationsaufkommens erscheint es hilfreich, die zwischenzeitlich eher verborgenen Elemente der Entscheidungstheorie wieder sichtbar zu machen. Dies ist fur das Verstandnis und die Einordnung der Methoden ebenso unerlasslich, wie fur die korrekte Anwendung. Logische Konsequenz daraus ist, die bisher eher getrennt betrachteten Bereiche der Entscheidungstheorie und der Investitionsrechnung so zusammenzufuhren, dass Gemeinsamkeiten und Querverbindungen zwischen den einzelnen Teilgebieten offengelegt werden koennen. Das auf diese Weise entstandene Sujet ist so umfangreich, dass eine Aufteilung in zwei Bande notwendig wurde.

David Muller nutzt das rationalitatsorientierte Investitionscontrolling als theoretische Grundlage zur bewussten Wahrnehmung und Integration der Flexibilitat im Verlauf von Investitionsfuhrungsprozessen in KMU. Durch die Verwendung von Realoptionsmodellen in allen Lebenszyklusphasen umweltfokussierter Investitionen wird die Quantifizierung und Berucksichtigung der Flexibilitat moglich.
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This is a reproduction of a book published before 1923. This book may have occasional imperfections such as missing or blurred pages, poor pictures, errant marks, etc. that were either part of the original artifact, or were introduced by the scanning process. We believe this work is culturally important, and despite the imperfections, have elected to bring it back into print as part of our continuing commitment to the preservation of printed works worldwide. We appreciate your understanding of the imperfections in the preservation process, and hope you enjoy this valuable book. ++++ The below data was compiled from various identification fields in the bibliographic record of this title. This data is provided as an additional tool in helping to ensure edition identification: ++++ De Rebvs Dvarvm Tribvvm Regni Ivdaici Adversis ... Johann David Muller Leipzig (J.c.E. Heinius, 1745 History; Jewish; History / Jewish; Jews

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