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Foundations of Programming, Statistics, and Machine Learning for Business Analytics
Business Analysts and Data Scientists are in huge demand, as global companies seek to digitally transform themselves and leverage their data resources to realize competitive advantage.This book covers all the fundamentals, from statistics to programming to business applications, to equip you with the solid foundational knowledge needed to progress in business analytics. Assuming no prior knowledge of programming or statistics, this book takes a simple step-by-step approach which makes potentially intimidating topics easy to understand, by keeping Maths to a minimum and including examples of business analytics in practice.Key features:· Introduces programming fundamentals using R and Python· Covers data structures, data management and manipulation and data visualization· Includes interactive coding notebooks so that you can build up your programming skills progressivelySuitable as an essential text for undergraduate and postgraduate students studying Business Analytics or as pre-reading for students studying Data Science.Ram Gopal is Pro-Dean and Professor of Information Systems at the University of Warwick.Daniel Philps is an Artificial Intelligence Researcher and Head of Rothko Investment Strategies.Tillman Weyde is Senior Lecturer at City, University of London.
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Basic Python for Data Management, Finance, and Marketing
Learn how to gather, manipulate, and analyze data with Python. This book is a practical guide to help you get started with Python from ground zero and to the point where you can use coding for everyday tasks. Python, the most in-demand skill by employers, can be learned in a matter of months and a working knowledge will help you to advance your career. This book will teach you to crunch numbers, analyze big-data, and switch from spreadsheets to a faster and more efficient programming language. You'll benefit from the numerous real-life examples designed to meet current world challenges and from step-by-step guidance to become a confident Python user. Python is used in all aspects of financial industry, from algo trading, reporting and risk management to building valuations models and predictive machine learning programs. Basic Python for Data Management, Finance, and Marketing highlights how this language has become a useful skill with digital marketers, allowing them to analyze data more precisely and run more successful campaigns.What You'll LearnGet started with Python from square oneExtend what's possible on excel with PythonAutomate tasks with PythonAnalyze data more preciselyWho This Book Is ForProfessionals who want to find a job in the modern world or advance their careers within field of Python programming language.
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Mathematical Programming with Data Perturbations
Presents research contributions and tutorial expositions on current methodologies for sensitivity, stability and approximation analyses of mathematical programming and related problem structures involving parameters. The text features up-to-date findings on important topics, covering such areas as the effect of perturbations on the performance of algorithms, approximation techniques for optimal control problems, and global error bounds for convex inequalities.
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Python for Finance 2e
The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks
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Introducing Python
Stuck in a coding conundrum? Whether you're an advanced beginner, an intermediate developer, or a curious newcomer, the complexities of coding can often feel like a labyrinth with no exit. With Python, however, you can start writing real code quickly-but where should you start?In this updated third edition, Bill Lubanovic acts as your personal guide to Python, offering a clear path through the intricacies and capabilities of this much-beloved coding language, including new chapters on AI models and performance enhancements. Easy to understand and enjoyable to read, this book not only teaches you the core concepts but also dives into practical applications that bridge the gap between learning and doing. By reading it, you will:Understand everything from basic data structures to advanced featuresGain insights into using Python for files, networking, databases, and data scienceLearn testing, debugging, code reuse, and other essential development tipsExplore how Python can be utilized in business, science, and the arts
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Foundations of Programming, Statistics, and Machine Learning for Business Analytics
Business Analysts and Data Scientists are in huge demand, as global companies seek to digitally transform themselves and leverage their data resources to realize competitive advantage.This book covers all the fundamentals, from statistics to programming to business applications, to equip you with the solid foundational knowledge needed to progress in business analytics. Assuming no prior knowledge of programming or statistics, this book takes a simple step-by-step approach which makes potentially intimidating topics easy to understand, by keeping Maths to a minimum and including examples of business analytics in practice.Key features:· Introduces programming fundamentals using R and Python· Covers data structures, data management and manipulation and data visualization· Includes interactive coding notebooks so that you can build up your programming skills progressivelySuitable as an essential text for undergraduate and postgraduate students studying Business Analytics or as pre-reading for students studying Data Science.Ram Gopal is Pro-Dean and Professor of Information Systems at the University of Warwick.Daniel Philps is an Artificial Intelligence Researcher and Head of Rothko Investment Strategies.Tillman Weyde is Senior Lecturer at City, University of London.
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Coding for Beginners: Using Python
A beginner’s guide to coding using Python, one of the most popular computer languages. Step-by-step instructions show how to get started and write a simple program. New commands are introduced with examples and colourful pictures so by the end of the book, readers can code games, drawings and more. Includes extra help and downloads online.
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Python for Beginners
Python is an amazing programming language. It can be applied to almost any programming task. It allows for rapid development and debugging. Getting started with Python is like learning any new skill: it’s important to find a resource you connect with to guide your learning. Luckily, there’s no shortage of excellent books that can help you learn both the basic concepts of programming and the specifics of programming in Python. With the abundance of resources, it can be difficult to identify which book would be best for your situation. Python for Beginners is a concise single point of reference for all material on python.Provides concise, need-to-know information on Python types and statements, special method names, built-in functions and exceptions, commonly used standard library modules, and other prominent Python toolsOffers practical advice for each major area of development with both Python 3.x and Python 2.xBased on the latest research in cognitive science and learning theoryHelps the reader learn how to write effective, idiomatic Python code by leveraging its best—and possibly most neglected—featuresThis book focuses on enthusiastic research aspirants who work on scripting languages for automating the modules and tools, development of web applications, handling big data, complex calculations, workflow creation, rapid prototyping, and other software development purposes. It also targets graduates, postgraduates in computer science, information technology, academicians, practitioners, and research scholars.
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Asynchronous Programming in Python
Take a practical journey through the core principles, concepts, and applications of asynchronous programming in Python across real-world environments and technologies.Key FeaturesUnderstand core principles and theory behind async programming in PythonMeasure the impact of async techniques in practical, real-world use casesApply async patterns in software design and data-oriented architecturesBook DescriptionAsynchronous programming is one of the most effective but often misunderstood techniques for building fast, scalable, and responsive systems in Python. While it can significantly improve performance, efficiency, and sustainability, using async without a clear understanding of its trade-offs can lead to fragile designs and hard-to-debug issues.This book offers a structured approach to applying asynchronous programming in Python. It begins with a conceptual framework to help you distinguish between synchronous and asynchronous execution models, and shows how async relates to other concurrency strategies such as multithreading and multiprocessing. From there, you will explore the core tools available for building async applications in Python.You will also learn how to measure the impact of async programming in practical scenarios, profile and debug asynchronous code, and evaluate performance improvements using real-world metrics. The final chapters focus on applying async techniques to common cloud-based systems, such as web frameworks, database interactions, and data-pipelines tools.Designed for developers looking to apply async programming with confidence, this book blends real-world examples with core concepts to help you write efficient, maintainable Python code.What you will learnUse generators, coroutines and async/await to build scalable Python functionsExplore event loops to manage concurrency and orchestrate async flowCompare concurrency models to choose the right async strategyOptimize I/O-intensive programs to improve system throughput and efficiencyBuild async services using real-world APIs and popular Python librariesApply structured concurrency and design patterns for cleaner async designTest and debug async Python code to ensure reliability and stabilityWho this book is forThis book will help Python developers who want to understand and apply the asynchronous programming model in application development, data analysis, and orchestration scenarios. Junior developers, data engineers,, and tech leads will also benefit from the application design examples.
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Student's Guide to the Study, Practice, and Tools of Modern Mathematics
A Student‘s Guide to the Study, Practice, and Tools of Modern Mathematics provides an accessible introduction to the world of mathematics. It offers tips on how to study and write mathematics as well as how to use various mathematical tools, from LaTeX and Beamer to Mathematica and Maple to MATLAB and R. Along with a color insert, the text includes exercises and challenges to stimulate creativity and improve problem solving abilities. The first section of the book covers issues pertaining to studying mathematics. The authors explain how to write mathematical proofs and papers, how to perform mathematical research, and how to give mathematical presentations. The second section focuses on the use of mathematical tools for mathematical typesetting, generating data, finding patterns, and much more. The text describes how to compose a LaTeX file, give a presentation using Beamer, create mathematical diagrams, use computer algebra systems, and display ideas on a web page. The authors cover both popular commercial software programs and free and open source software, such as Linux and R. Showing how to use technology to understand mathematics, this guide supports students on their way to becoming professional mathematicians. For beginning mathematics students, it helps them study for tests and write papers. As time progresses, the book aids them in performing advanced activities, such as computer programming, typesetting, and research.
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Python Programming Professional Made Easy
Python Programming Professional Made Easy 2nd Edition! Sam Key back at it again with his upgraded version of Python Going from beginner to professional? Want to skip the learning curve? Need the jargon removed so you can understand in your terms? From various programming languages to statements and Basic Operators Everything you need to know with functions and flow controls! Don't waste anytime and jump on board of Python! Start your programming right now!
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Programming and Mathematical Method
The Summer School in Marktoberdorf 1990 had as its overall theme the development of programs as an activity that can be carried out based on and supported by a mathematical method. In particular mathematical methods for the development of programs as parts of distributed systems were included. Mathematical programming methods are a very important topic for which a lot of research in recent years has been carried out. In the Marktoberdorf Summer School outstanding scientists lectured on mathematical programming methods. The lectures centred around logical and functional calculi for the • specification, • refinement, • verification of programs and program systems. Some extremely remarkable examples were given. Looking at these examples it becomes clear that proper research and teaching in the area of program methodology should always show its value by being applied at least to small examples or case studies. It is one of the problems of computing science that examples and case studies have to be short and small to be lJresentable in lectures and papers of moderate size. However, even small examples can tell a lot about the tractability and adequacy of methods and being able to treat small examples does at least prove that the method can be applied in modest ways. Furthermore it demonstrates to some extent the notational and calculational overhead of applying formal methods.
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Python for the Busy Java Developer
Are you a seasoned Java developer who wishes to learn Python? Perhaps you’ve just joined a project where a chunk of system integration code is written in Python. Or maybe you need to implement a report generation module in the next sprint and your colleague mentioned that Python would be the perfect tool for the job. In any case, if you are in a situation where you have to pick up the Python programming language overnight, this book is just for you! Hit the ground running and gain a fast-paced overview of what the Python language is all about, the syntax that it uses and the ecosystem of libraries and tools that surround the language. This concise book doesn’t spend time on details from an introductory programming course or document every single Python feature. Instead, Python for the Busy Java Developer is designed for experienced Java developers to obtain sufficient familiarity with the language and dive into coding, quickly. What You'll LearnDiscover the fundamentals of the core Python language and how they compare to JavaUnderstand Python syntax and the differences between Python 2.x and 3.xExplore the Python ecosystem, its standard libraries, and how to implement themWho This Book Is ForWorking programmers who are comfortable with Java or another object-oriented programming language such as C#
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