Machine Learning in Quantitative Finance: History, Theory and Applications, William McGhee
Автор: Gebrail Bekda, Sinan Melih Nigdeli Название: Artificial intelligence and machine learning applications in civil, mechanical, and industrial engineering ISBN: 1799803023 ISBN-13(EAN): 9781799803027 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 198530.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Presents innovative research on the methods and implementation of machine learning and AI in multiple facets of engineering. While highlighting topics including control devices, geotechnology, and artificial neural networks, this book is designed for engineers, academics, researchers, practitioners, and students.
As data holdings get bigger and questions get harder, data scientists and analysts must focus on the systems, the tools and techniques, and the disciplined process to get the correct answer, quickly Whether you work within industry or government, this book will provide you with a foundation to successfully and confidently process large amounts of quantitative data.
Here are just a dozen of the many questions answered within these pages:
What does quantitative analysis of a system really mean?
What is a system?
What are big data and analystics?
How do you know your numbers are good?
What will the future data science environment look like?
How do you determine data provenance?
How do you gather and process information, and then organize, store, and synthesize it?
How does an organization implement data analytics?
Do you really need to think like a Chief Information Officer?
What is the best way to protect data?
What makes a good dashboard?
What is the relationship between eating ice cream and getting attacked by a shark?
The nine chapters in this book are arranged in three parts that address systems concepts in general, tools and techniques, and future trend topics. Systems concepts include contrasting open and closed systems, performing data mining and big data analysis, and gauging data quality. Tools and techniques include analyzing both continuous and discrete data, applying probability basics, and practicing quantitative analysis such as descriptive and inferential statistics. Future trends include leveraging the Internet of Everything, modeling Artificial Intelligence, and establishing a Data Analytics Support Office (DASO).
Many examples are included that were generated using common software, such as Excel, Minitab, Tableau, SAS, and Crystal Ball. While words are good, examples can sometimes be a better teaching tool. For each example included, data files can be found on the companion website. Many of the data sets are tied to the global economy because they use data from shipping ports, air freight hubs, largest cities, and soccer teams. The appendices contain more detailed analysis including the 10 T's for Data Mining, Million Row Data Audit (MRDA) Processes, Analysis of Rainfall, and Simulation Models for Evaluating Traffic Flow.
Автор: Deka, Paresh Chandra, Название: A primer on machine learning applications in civil engineering / ISBN: 113832339X ISBN-13(EAN): 9781138323391 Издательство: Taylor&Francis Рейтинг: Цена: 100030.00 T Наличие на складе: Нет в наличии. Описание: This book provides a broad overview of the available machine learning techniques for solving civil engineering problems including drought forecasting, river flow forecasting, precipitation forecasting, and significant wave height forecasting. Fundamentals of both theoretical and practical aspects are discussed in varied domains.
Автор: Lesley Martha Название: Machine Vision and Its Applications ISBN: 1632403323 ISBN-13(EAN): 9781632403322 Издательство: Неизвестно Цена: 183860.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Название: Machine intelligence and knowledge engineering for robotic applications ISBN: 3642873898 ISBN-13(EAN): 9783642873898 Издательство: Springer Рейтинг: Цена: 74490.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Proceedings of the NATO Advanced Research Workshop on Machine Intelligence and Knowledge Engineering for Robotic Applications held at Maratea, Italy, May 12-16, 1986
Автор: Michael M. Richter; Sheuli Paul Название: Signal Processing and Machine Learning with Applications ISBN: 3319453718 ISBN-13(EAN): 9783319453712 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Signal processing captures, interprets, describes and manipulates physical phenomena. Mathematics, statistics, probability, and stochastic processes are among the signal processing languages we use to interpret real-world phenomena, model them, and extract useful information. This book presents different kinds of signals humans use and applies them for human machine interaction to communicate. Signal Processing and Machine Learning with Applications presents methods that are used to perform various Machine Learning and Artificial Intelligence tasks in conjunction with their applications. It is organized in three parts: Realms of Signal Processing; Machine Learning and Recognition; and Advanced Applications and Artificial Intelligence. The comprehensive coverage is accompanied by numerous examples, questions with solutions, with historical notes. The book is intended for advanced undergraduate and postgraduate students, researchers and practitioners who are engaged with signal processing, machine learning and the applications.
Автор: Oleg Okun; Giorgio Valentini; Matteo Re Название: Ensembles in Machine Learning Applications ISBN: 3662507064 ISBN-13(EAN): 9783662507063 Издательство: Springer Рейтинг: Цена: 113180.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book collects papers from the 3rd Workshop on Supervised and Unsupervised Ensemble Methods and their Applications (SUEMA), held as part of the 2010 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases.
Автор: Alan H. Fielding Название: Machine Learning Methods for Ecological Applications ISBN: 1461374138 ISBN-13(EAN): 9781461374138 Издательство: Springer Рейтинг: Цена: 148020.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This is the first text aimed at introducing machine learning methods to a readership of professional ecologists. All but one of the chapters have been written by ecologists and biologists who highlight the application of a particular method to a particular class of problem.
Автор: Christine Preisach; Hans Burkhardt; Lars Schmidt-T Название: Data Analysis, Machine Learning and Applications ISBN: 3540782397 ISBN-13(EAN): 9783540782391 Издательство: Springer Рейтинг: Цена: 186290.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Contains the selected papers in the field of data analysis, machine learning and applications presented during the 31st Annual Conference of the German Classification Society (Gesellschaft fur Klassifikation - GfKl), which was held at the Albert-Ludwigs-University in Freiburg, Germany, in March 2007.
Автор: Larisa Angstenberger Название: Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering ISBN: 9048157757 ISBN-13(EAN): 9789048157754 Издательство: Springer Рейтинг: Цена: 153720.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering focuses on fuzzy clustering methods which have proven to be very powerful in pattern recognition and considers the entire process of dynamic pattern recognition.
Автор: Aboul Ella Hassanien; Abdel-Badeeh M. Salem; Rabie Название: Advanced Machine Learning Technologies and Applications ISBN: 3642353258 ISBN-13(EAN): 9783642353253 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book constitutes the refereed proceedings of the First International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2012, held in Cairo, Egypt, in December 2012.
Take your Python machine learning ideas and create serverless web applications accessible by anyone with an Internet connection. Some of the most popular serverless cloud providers are covered in this book--Amazon, Microsoft, Google, and PythonAnywhere.
You will work through a series of common Python data science problems in an increasing order of complexity. The practical projects presented in this book are simple, clear, and can be used as templates to jump-start many other types of projects. You will learn to create a web application around numerical or categorical predictions, understand the analysis of text, create powerful and interactive presentations, serve restricted access to data, and leverage web plugins to accept credit card payments and donations. You will get your projects into the hands of the world in no time.
Each chapter follows three steps: modeling the right way, designing and developing a local web application, and deploying onto a popular and reliable serverless cloud provider. You can easily jump to or skip particular topics in the book. You also will have access to Jupyter notebooks and code repositories for complete versions of the code covered in the book.
What You'll Learn
Extend your machine learning models using simple techniques to create compelling and interactive web dashboards
Leverage the Flask web framework for rapid prototyping of your Python models and ideas
Create dynamic content powered by regression coefficients, logistic regressions, gradient boosting machines, Bayesian classifications, and more
Harness the power of TensorFlow by exporting saved models into web applications
Create rich web dashboards to handle complex real-time user input with JavaScript and Ajax to yield interactive and tailored content
Create dashboards with paywalls to offer subscription-based access
Access API data such as Google Maps, OpenWeather, etc.
Apply different approaches to make sense of text data and return customized intelligence
Build an intuitive and useful recommendation site to add value to users and entice them to keep coming back
Utilize the freemium offerings of Google Analytics and analyze the results
Take your ideas all the way to your customer's plate using the top serverless cloud providers
Who This Book Is For
Those with some programming experience with Python, code editing, and access to an interpreter in working order. The book is geared toward entrepreneurs who want to get their ideas onto the web without breaking the bank, small companies without an IT staff, students wanting exposure and training, and for all data science professionals ready to take things to the next level.
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