Analiza danych
Alexandre Alves, Lloyd Williams, Robin J. Smith
Events are everywhere, events which can have positive or negative impacts on our lives and important business decisions. These events can impact a company's success, failure, and profitability. Technology now allows people from all walks of life to create Event Driven applications that will immediately and completely respond to the events that affect you and your business. So you are much more responsive to your customers, and competitive threats, and can take advantage of transient time sensitive situations. Getting Started with Oracle Event Processing will let you benefit from the skills and years of experience from the original pioneers who were the driving force behind this immensely flexible, complete, and award winning Event Stream Processing technology. It provides all of the information needed to rapidly deliver and understand Event Driven Architecture (EDA) Applications. These can then be executed on the comprehensive and powerful integral Java Event Server platform which utilizes the hardware and operating system.After an introduction into the benefits and uses of Event Stream Processing, this book uses tutorials and practical examples to teach you how to create valuable and rewarding Event Driven foundational applications. First you will learn how to solve Event Stream Processing problems, followed by the fundamentals of building an Oracle Event processing application in a step by step fashion. Exciting and unique topics are then covered: application construction, the powerful capabilities of the Oracle Event Processing language, CQL, monitoring and managing these applications, and the fascinating domain of real-time Geospatial Movement Analysis. Getting Started with Oracle Event Processing will provide a unique perspective on product creation, evolution and a solid understanding on how to effectively use the product.
Phuong Vo.T.H, Martin Czygan
Data analysis is the process of applying logical and analytical reasoning to study each component of data. Python is a multi-domain, high-level, programming language. It’s often used as a scripting language because of its forgiving syntax and operability with a wide variety of different eco-systems. Python has powerful standard libraries or toolkits such as Pylearn2 and Hebel, which offers a fast, reliable, cross-platform environment for data analysis.With this book, we will get you started with Python data analysis and show you what its advantages are.The book starts by introducing the principles of data analysis and supported libraries, along with NumPy basics for statistic and data processing. Next it provides an overview of the Pandas package and uses its powerful features to solve data processing problems.Moving on, the book takes you through a brief overview of the Matplotlib API and some common plotting functions for DataFrame such as plot. Next, it will teach you to manipulate the time and data structure, and load and store data in a file or database using Python packages. The book will also teach you how to apply powerful packages in Python to process raw data into pure and helpful data using examples.Finally, the book gives you a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or build helpful products, such as recommendations and predictions using scikit-learn.
Luca Zamboni
Simulink is an engineer's Swiss army knife: instead of spending the day typing out complex formulas, Simulink enables you to both draw and execute them. Block after block, you can develop your ideas without struggling with obscure programming languages and you don't have to wait to debug your algorithm - just launch a simulation!Getting Started with Simulink will give you comprehensive knowledge of Simulink's capabilities. From the humble constant block to the S-function block, you will have a clear understanding of what modelling really means, without feeling that something has been left out. By the time you close the book, you'll be able to further extend your modelling skills without any help.We''ll start with a brief introduction, and immediately start placing the first blocks. Little by little, you'll build a car cruise controller model, followed by the mathematical model of a sports car in order to calibrate it. Then you'll learn how to interface your Simulink model with the external world. This book will give you an easy understanding of the tools Simulink offers you, guiding you through a complex exercise split into the three main phases of Simulink development: modelling, testing, and interfacing.
Tyler Richards
Streamlit shortens the development time for the creation of data-focused web applications, allowing data scientists to create web app prototypes using Python in hours instead of days. Getting Started with Streamlit for Data Science takes a hands-on approach to helping you learn the tips and tricks that will have you up and running with Streamlit in no time.You'll start with the fundamentals of Streamlit by creating a basic app and gradually build on the foundation by producing high-quality graphics with data visualization and testing machine learning models. As you advance through the chapters, you’ll walk through practical examples of both personal data projects and work-related data-focused web applications, and get to grips with more challenging topics such as using Streamlit Components, beautifying your apps, and quick deployment of your new apps.By the end of this book, you’ll be able to create dynamic web apps in Streamlit quickly and effortlessly using the power of Python.
Tristan Guillevin
Tableau is one of the leading business intelligence tools used worldwide, in organizations of every scale. In its latest release, Tableau 2018 promises richer and more useful features related to visual analytics, reporting, dashboarding, and a host of other data visualization aspects. Getting Started with Tableau 2018.x will get you up and running with these features.The book starts with all the new functionalities of the different Tableau 2018 versions, along with concrete examples of how to use them. However, if you're new to Tableau, don't worry! The rest of the book will guide you through each major aspect of Tableau with examples. You'll learn how to connect to data, build a data source, visualize your data, build a dashboard, and share it online. In the final chapters, you'll also learn advanced techniques such as creating a cross-database join, data blending, and more.By the end of the book, you will have a firm understanding of how to effectively use Tableau to create quick, cost-effective, and business-efficient business intelligence solutions.
Tristan Guillevin
Tableau is one of the leading data visualization tools and is regularly updated with new functionalities and features. The latest release, Tableau 2019.2, promises new and advanced features related to visual analytics, reporting, dashboarding, and a host of other data visualization aspects. Getting Started with Tableau 2019.2 will get you up to speed with these additional functionalities.The book starts by highlighting the new functionalities of Tableau 2019.2, providing concrete examples of how to use them. However, if you're new to Tableau, you won't have to worry as the book also covers the major aspects of Tableau with relevant examples. You'll learn how to connect to data, build a data source, visualize your data, build a dashboard, and even share data online. In the concluding chapters, you'll delve into advanced techniques such as creating a cross-database join and data blending.By the end of this book, you will be able to use Tableau effectively to create quick, cost-effective, and business-efficient Business Intelligence (BI) solutions.
Donato Teutonico
This book is perfect for R programmers who are interested in learning to use ggplot2 for data visualization, from the basics up to using more advanced applications, such as faceting and grouping. Since this book will not cover the basics of R commands and objects, you should have a basic understanding of the R language.
Go Design Patterns. Best practices in software development and CSP
Mario Castro Contreras
Go is a multi-paradigm programming language that has built-in facilities to create concurrent applications. Design patterns allow developers to efficiently address common problems faced during developing applications. Go Design Patterns will provide readers with a reference point to software design patterns and CSP concurrency design patterns to help them build applications in a more idiomatic, robust, and convenient way in Go. The book starts with a brief introduction to Go programming essentials and quickly moves on to explain the idea behind the creation of design patterns and how they appeared in the 90’s as a common language between developers to solve common tasks in object-oriented programming languages. You will then learn how to apply the 23 Gang of Four (GoF) design patterns in Go and also learn about CSP concurrency patterns, the killer feature in Go that has helped Google develop software to maintain thousands of servers. With all of this the book will enable you to understand and apply design patterns in an idiomatic way that will produce concise, readable, and maintainable software.