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Thinking Clearly with Data: A Guide to Quantitative Reasoning and Analysis

Автор: Limpopo5 от 2022-01-22, 21:24:01
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Thinking Clearly with Data: A Guide to Quantitative Reasoning and AnalysisНазвание: Thinking Clearly with data: A Guide to Quantitative Reasoning and Analysis
Автор: Ethan Bueno de Mesquita, Anthony Fowler
Издательство: Princeton University Press
Год: 2021
Страниц: 400
Язык: английский
Формат: pdf, epub
Размер: 10.0 MB

An engaging introduction to Data Science that emphasizes critical thinking over statistical techniques. An introduction to Data Science or statistics shouldn’t involve proving complex theorems or memorizing obscure terms and formulas, but that is exactly what most introductory quantitative textbooks emphasize. In contrast, Thinking Clearly with Data focuses, first and foremost, on critical thinking and conceptual understanding in order to teach students how to be better consumers and analysts of the kinds of quantitative information and arguments that they will encounter throughout their lives.

Event- and Data-Centric Enterprise Risk-Adjusted Return Management: A Banking Practitioner’s Handbook

Автор: Limpopo5 от 2022-01-04, 08:41:51
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Event- and Data-Centric Enterprise Risk-Adjusted Return Management: A Banking Practitioner’s HandbookНазвание: Event- and Data-Centric Enterprise Risk-Adjusted Return Management: A Banking Practitioner’s Handbook
Автор: Kannan Subramanian R., Dr. Sudheesh Kumar Kattumannil
Издательство: Apress
Год: 2022
Страниц: 1112
Язык: английский
Формат: pdf (true)
Размер: 72.2 MB

The book provides guidance on the underlying knowledge areas of banking, enterprise risk management, enterprise architecture, technology, event management, processes, and Data Science. The first part of the book explains the current state of banking architecture and its limitations. After defining a target model, it explains an approach to determine the "gap" and the second part of the book guides banks on how to implement the enterprise risk-adjusted return model. Data virtualization (DV) can unify both structured and unstructured data in real-time to power the ERR model. DV has grown in its usage and is a critical part of modern enterprise data architectures. Data as a service (DaaS) is a business-centric service that delivers data assets on demand using a standard connectivity protocol in a predetermined, configurable format and frequency. DV can be exploited by enabling DaaS for data democratization and decision making. Machine learning (ML) and deep learning algorithms are finding more use cases in risk management and in general banking functions. Banks with large derivative portfolios have been early adopters as ML is good at managing non-linear relationships between explanatory variables and explained variables. ML can improve accuracy as be applied for a broader set of variables.

Data Analysis for Business, Economics, and Policy

Автор: Limpopo5 от 2021-11-13, 21:29:14
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Data Analysis for Business, Economics, and PolicyНазвание: Data Analysis for Business, Economics, and Policy
Автор: Gabor Bekes, Gabor Kezdi
Издательство: Cambridge University Press
Год: 2021
Страниц: 742
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, Machine Learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at site.

Mining Complex Networks

Автор: Limpopo5 от 2021-11-12, 13:56:00
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Mining Complex NetworksНазвание: Mining Complex Networks
Автор: Bogumił Kaminski, Paweł Prałat
Издательство: CRC Press
Год: 2022
Страниц: 278
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

This book concentrates on mining networks, a subfield within data science. Data science uses scientific and computational tools to extract valuable knowledge from large data sets. Once data is processed and cleaned, it is analyzed and presented to support decision-making processes. Data science and machine learning tools have become widely used in companies of all sizes. Networks are often large-scale, decentralized, and evolve dynamically over time. Mining complex networks aim to understand the principles governing the organization and the behavior of such networks is crucial for a broad range of fields of study. Here are a few selected typical applications of mining networks: Jupiter notebooks (in Python and Julia) accompany the book and can be accessed on site.

It's All Analytics - Part II: Designing an Integrated AI, Analytics, and Data Science Architecture for Your Organization

Автор: Limpopo5 от 2021-08-01, 23:07:42
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It's All Analytics - Part II: Designing an Integrated AI, Analytics, and Data Science Architecture for Your OrganizationНазвание: It's All Analytics - Part II: Designing an Integrated AI, Analytics, and Data Science Architecture for Your Organization
Автор: Scott Burk, David E. Sweenor
Издательство: Routledge
Год: 2022
Страниц: 299
Язык: английский
Формат: pdf (true)
Размер: 10.19 MB

This book debunks the common notion that data are the foundation of any analysis. It shows that a much more basic foundation is needed before results of data analysis can be used in an organization effectively - appropriate business processes must be designed and built to accept them. The question is posed early in the book, “We have to change the way we work”? Yes, we must change the way we work. That has happened many times before. It happened during the Industrial Revolution to harness steam power to drive big machines. It happened during the Computer Revolution to move from typewriters to word processors and from paper ledgers to computer databases. AI and analytics programs are considered something you “add to your business or organization” - a department, some data scientists, some software, and some training.

97 Things Every Data Engineer Should Know: Collective Wisdom from the Experts (Final)

Автор: Limpopo5 от 2021-06-13, 04:02:30
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97 Things Every Data Engineer Should Know: Collective Wisdom from the Experts (Final)Название: 97 Things Every Data Engineer Should Know: Collective Wisdom from the Experts (Final)
Автор: Tobias Macey
Издательство: O’Reilly Media, Inc.
Год: 2021
Страниц: 250
Язык: английский
Формат: epub
Размер: 51.8 MB

Data engineering as a distinct role is relatively new, but the responsibilities have existed for decades. Broadly speaking, a data engineer makes data available for use in analytics, machine learning, business intelligence, etc. The introduction of big data technologies, data science, distributed computing, and the cloud have all contributed to making the work of the data engineer more necessary, more complex, and (paradoxically) more possible. It is an impossible task to write a single book that encompasses everything that you will need to know to be effective as a data engineer, but there are still a number of core principles that will help you in your journey.

Industry 4.0, AI, and Data Science

Автор: Limpopo5 от 2021-06-05, 15:27:38
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Industry 4.0, AI, and Data ScienceНазвание: Industry 4.0, AI, and Data Science
Автор: Vikram Bali, Kakoli Banerjee, Narendra Kumar
Издательство: CRC Press
Год: 2022
Страниц: 283
Язык: английский
Формат: pdf (true)
Размер: 47.0 MB

The aim of this book is to provide insight into Data Science and Artificial Learning Techniques based on Industry 4.0, conveys how Machine Learning & Data Science are becoming an essential part of industrial and academic research. Varying from healthcare to social networking and everywhere hybrid models for Data Science, Al, and Machine Learning are being used. The book describes different theoretical and practical aspects and highlights how new systems are being developed.

Python for Data Analysis: Data Wrangling with Pandas, NumPy, and Jupyter, 3rd Edition (Early Release)

Автор: Limpopo5 от 2021-05-27, 21:37:27
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Python for Data Analysis: Data Wrangling with Pandas, NumPy, and Jupyter, 3rd Edition (Early Release)Название: Python for Data Analysis: Data Wrangling with Pandas, NumPy, and Jupyter, 3rd Edition (Early Release)
Автор: Wes McKinney
Издательство: O’Reilly Media, Inc.
Год: 2021-05-26
Язык: английский
Формат: epub
Размер: 10.1 MB

Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.9 and pandas 1.2, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, and Jupyter in the process. This book is concerned with the nuts and bolts of manipulating, processing, cleaning, and crunching data in Python. My goal is to offer a guide to the parts of the Python programming language and its data-oriented library ecosystem and tools that will equip you to become an effective data analyst.

Data Science for Business Professionals: A Practical Guide for Beginners

Автор: Limpopo5 от 2021-05-23, 21:08:57
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Data Science for Business Professionals: A Practical Guide for BeginnersНазвание: Data Science for Business Professionals: A Practical Guide for Beginners
Автор: Probyto Data Science and Consulting Pvt. Ltd.
Издательство: BPB Publications
Год: 2020
Страниц: 366
Язык: английский
Формат: epub
Размер: 12.7 MB

Primer into the multidisciplinary world of Data Science. The book will initially explain the What-Why of Data Science and the process of solving a Data Science problem. The fundamental concepts of Data Science, such as Statistics, Machine Learning, Business Intelligence, Data pipeline, and Cloud Computing, will also be discussed. All the topics will be explained with an example problem and will show how the industry approaches to solve such a problem. The book will pose questions to the learners to solve the problems and build the problem-solving aptitude and effectively learn. The book uses Mathematics wherever necessary and will show you how it is implemented using Python with the help of an example dataset.

Everyday Data Science: Optimize Your Life

Автор: Limpopo5 от 2021-05-17, 03:17:58
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Everyday Data Science: Optimize Your LifeНазвание: Everyday Data Science: Optimize Your Life
Автор: Andrew N Carr
Издательство: Independently published
Год: 2021
Страниц: 94
Язык: английский
Формат: pdf (true)
Размер: 11.2 MB

Everyday data science is a collection of tools and techniques you can use to master data science in your day-to-day life. There are case studies, tutorials, code snippets, pictures, math, and jokes. All designed as a fun introduction to the world of data science. Some example chapters include, Life is full of decisions. We, as people, have the remarkable ability to make decisions in the face of uncertainty. We, as humans, have only recently developed the ability to use computers to process vast amounts of data to improve our decision making. This innovation has led to the development of the field of Data Science. This book is written to give tools and inspiration to aspiring decision makers. You make decisions daily and the methodology of data science can help.

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