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C++ Crash Course
C++ Crash Course

C++ is one of the most widely used languages for real-world software. In the hands of a knowledgeable programmer, C++ can produce small, efficient, and readable code that any programmer would be proud of. Designed for intermediate to advanced programmers, C++ Crash Course cuts through the weeds to get you straight to the core of C++17, the most modern revision of the ISO standard. Part 1 covers the core of the C++ language, where you'll learn about everything from types and functions, to the object life cycle and expressions. Part 2 introduces you to the C++ Standard Library and Boost Libraries, where you'll learn about all of the high-quality, fully-featured facilities available to you. You'll cover special utility classes, data structures, and algorithms, and learn how to manipulate file systems and build high-performance programs that communicate over networks. You'll learn all the major features of modern C++, including: Fundamental types, reference types, and user-defined ty ...
Data Analysis with Python
Data Analysis with Python

Data Analysis with Python offers a modern approach to data analysis so that you can work with the latest and most powerful Python tools, AI techniques, and open source libraries. Industry expert David Taieb shows you how to bridge data science with the power of programming and algorithms in Python. You'll be working with complex algorithms, and cutting-edge AI in your data analysis. Learn how to analyze data with hands-on examples using Python-based tools and Jupyter Notebook. You'll find the right balance of theory and practice, with extensive code files that you can integrate right into your own data projects. Explore the power of this approach to data analysis by then working with it across key industry case studies. Four fascinating and full projects connect you to the most critical data analysis challenges you're likely to meet in today. The first of these is an image recognition application with TensorFlow - embracing the importance today of AI in your data analysis. The secon ...
Integrating Serverless Architecture
Integrating Serverless Architecture

Design, develop, build, and deliver an end-to-end serverless architecture by leveraging Azure services, frameworks, and tools. This book offers a holistic approach, guiding you through the design and development of a Twitter Bot application, while leveraging Azure Functions. Integrating Serverless Architecture begins with an overview of serverless computing and getting started with Azure Functions. Here, you will create a Twitter bot function which scans Twitter for the latest tweets and makes use of dependency injection. Further, you will learn about Azure Cosmos DB where you will cover its change feed mechanism and the repository pattern. You will create a Cosmos DB trigger-based tweet notifier function, which will broadcast the latest tweets to connected clients. You will explore the basics of Azure Service Bus and create a tweet scheduler function, which will prioritize different keywords for the Twitter bot function. Along the way, you will debug, deliver, and test the function ...
Mining Social Media
Mining Social Media

Did fake Twitter accounts help sway a presidential election? What can Facebook and Reddit archives tell us about human behavior? In Mining Social Media, senior BuzzFeed reporter Lam Thuy Vo shows you how to use Python and key data analysis tools to find the stories buried in social media. Whether you're a professional journalist, an academic researcher, or a citizen investigator, you'll learn how to use technical tools to collect and analyze data from social media sources to build compelling, data-driven stories. Learn how to: Write Python scripts and use APIs to gather data from the social web; Download data archives and dig through them for insights; Inspect HTML downloaded from websites for useful content; Format, aggregate, sort, and filter your collected data using Google Sheets; Create data visualizations to illustrate your discoveries; Perform advanced data analysis using Python, Jupyter Notebooks, and the pandas library; Apply what you've learned to research topics on you ...
Quick Start Guide to Dart Programming
Quick Start Guide to Dart Programming

Get started with Dart and learn to program with this language suitable for high-performing, modern applications. You'll gain the basics and be ready to move to the next level: web and mobile apps. While you won't learn the specifics of programming web and mobile apps, you will have the foundation to take your Dart skills in that direction. This book starts with an introduction to the Dart IDE, after which you will take a look at the various components of the Dart programming language. You will look at types and variables, and get to know the significance of collections and arrays in Dart. Once you've familiarized yourself with the initial components of Dart, you will see how flow of control and looping can be achieved by using if, else, and conditional expressions. Moving on to functions and objects, you will dig deeper into the concepts of object oriented programming to gauge the importance of constructors in Dart. You will then discover more about inheritance and mixins, seeing ho ...
Practical Data Science with R, 2nd Edition
Practical Data Science with R, 2nd Edition

Practical Data Science with R, Second Edition takes a practice-oriented approach to explaining basic principles in the ever expanding field of data science. You'll jump right to real-world use cases as you apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support. Evidence-based decisions are crucial to success. Applying the right data analysis techniques to your carefully curated business data helps you make accurate predictions, identify trends, and spot trouble in advance. The R data analysis platform provides the tools you need to tackle day-to-day data analysis and machine learning tasks efficiently and effectively. Practical Data Science with R, 2nd Edition is a task-based tutorial that leads readers through dozens of useful, data analysis practices using the R language. By concentrating on the most important tasks you'll face on the job, this friendly guide is comfort ...
Data Science from Scratch, 2nd Edition
Data Science from Scratch, 2nd Edition

To really learn data science, you should not only master the tools - data science libraries, frameworks, modules, and toolkits - but also understand the ideas and principles underlying them. Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with the hacking skills you need to get started as a data scientist. Packed with new material on deep learning, statistics, and natural language processing, this updated book shows you how to find the gems in today's messy glut of data. Get a crash course in Python; Learn the basics of linear algebra, statistics, and probability - and how and when they're used in data science; Collect, explore, clean, munge, and manipulate data; Dive into the fundamentals of machine ...
Practical Time Series Analysis
Practical Time Series Analysis

Time series data analysis is increasingly important due to the massive production of such data through the internet of things, the digitalization of healthcare, and the rise of smart cities. As continuous monitoring and data collection become more common, the need for competent time series analysis with both statistical and machine learning techniques will increase. Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challenges in time series, using both traditional statistical and modern machine learning techniques. Author Aileen Nielsen offers an accessible, well-rounded introduction to time series in both R and Python that will have data scientists, software engineers, and researchers up and running quickly. You'll get the guidance you need to confidently: Find and wrangle time series data; Undertake exploratory time series data analysis; Store temporal data ...
Programming C# 8.0
Programming C# 8.0

C# is undeniably one of the most versatile programming languages available to engineers today. With this comprehensive guide, you'll learn just how powerful the combination of C# and .NET can be. Author Ian Griffiths guides you through C# 8.0 fundamentals and techniques for building cloud, web, and desktop applications. Designed for experienced programmers, this book provides many code examples to help you work with the nuts and bolts of C#, such as generics, LINQ, and asynchronous programming features. You'll get up to speed on .NET Core and the latest C# 8.0 additions, including asynchronous streams, nullable references, pattern matching, default interface implementation, ranges and new indexing syntax, and changes in the .NET tool chain. Discover how C# supports fundamental coding features, such as classes, other custom types, collections, and error handling; Learn how to write high-performance memory-efficient code with .NET Core's Span and Memory types; Query and process div ...
Beginning Microsoft Power BI
Beginning Microsoft Power BI

Analyze company data quickly and easily using Microsoft's powerful data tools. Learn to build scalable and robust data models, clean and combine different data sources effectively, and create compelling and professional visuals. Beginning Power BI is a hands-on, activity-based guide that takes you through the process of analyzing your data using the tools that that encompass the core of Microsoft's self-service BI offering. Starting with Power Query, you will learn how to get data from a variety of sources, and see just how easy it is to clean and shape the data prior to importing it into a data model. Using Power BI tabular and the Data Analysis Expressions (DAX), you will learn to create robust scalable data models which will serve as the foundation of your data analysis. From there you will enter the world of compelling interactive visualizations to analyze and gain insight into your data. You will wrap up your Power BI journey by learning how to package and share your reports an ...
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