.Net Data Science

Gain insights from your data quicker and easier than ever before using your own C#! About This Book This easy-to-follow guide will help you enter the field of Data Science with C# Learn to use various .NET APIs and perform exploratory data analysis that starts with a few data journalism questions and ends with intuitive visualizations Explore the power of C#'s cool Data Science libraries and learn to perform complex computations using this hands-on guide! Who This Book Is ForIf you are a seasoned C# developer with knowledge of the Microsoft technology stack and a good background in mathematics, then this book is for you. A basic understanding of statistics and probability is necessary to get the most out of this book. This book will also be useful for those data scientists who want to know how to perform data analysis with C#. What you will learn Be reintroduced to the world of .NET statistics and calculus libraries and frameworks Overcome the pitfalls of modeling your data for simple to complex analysis Use the tools to utilize the statistical models for designing custom Machine Learning applications Know how to deal with high volumes of data and scale your ASP.NET application to match the performance requirements of your Data Science application Integrate various tools such as ATOM (ASP.NET MVC), Data Science libraries such as Accord.NET, Python's Natural Language Toolkit, and SWIRL to achieve precise data manipulations and intuitive visualizations Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and deep learning In DetailData Science is a new field that is still being defined. It's existed largely in academia and “start-ups,” yet stands at the core of the world's most important, fun, and useful software. Because it was traditionally done in an elite academic setting, proprietary software was not included. With Microsoft taking a much more different approach with licensing, Data Science can easily be done with Microsoft tools and is now readily available to C# developers. This book will re-introduce you to the important parts of statistics and probabilities. From there, we move on to how to apply these principles using C# and C# based libraries. This includes using purely Microsoft technologies such as SSRS, SSIS, PowerShell, SSAS, as well as integrating various .NET libraries available for Data Science. Once you have realized the potential of various libraries, we'll dive deeper in to implementing concepts of regression, inference, correlation, and causation to devise empirical evidence from your data sets and visualize it. Towards the end of the book, you will learn to implement supervised, unsupervised, and deep learning algorithms and techniques that can be applied to a wide range of real-world problems.

About the Author :
William Ryan 'Bill' is a seasoned .NET developer and Data Scientist. He has participated or authored over 4 books, and he's been the lead technical reviewer on 16 different books. He's worked with Microsoft and other industry leaders developing over 70 different certification exams in his career. He's been voted Microsoft's Most Valuable professional in multiple categories for 9 years. He's built two different Data Science departments and currently leads a department at a major insurance corporation that oversees almost 600 million dollars in annual revenue. This includes the consolidation and analysis of over 25 different corporations all ranging in 25 million dollars a year in revenue to 400 million. He has a strong understanding of Microsoft, IBM, and Oracle technologies as well as several of the common NoSQL databases. He has been heavily involved in the Internet of Things (IOT) since well before it became popular. He's been working with Artificial Intelligence since the mid 90s and has used Statistical Models to help detect and reduce fraud in real-time for several major corporations that you likely interact with several times a day. He's a Drone enthusiast and has written well over 300 bots and web spiders. He's very well versed in continuous integration and is particular well versed in writing this book because he's resisted the urge to become a technology partisan. While he prefers to live in the world of Functional Programming and NO-SQL, he's spent a good part of his career using Object-Oriented Programming and SQL-based data stores. He is affectionately known as a true SQL Wonk, being one of the few people that can easily discuss each of Codd's normal forms from memory.