C# Machine Learning Projects torrent

Machine learning is applied in almost all kinds of real-world surroundings and industries, right from medicine to advertising; from finance to scientifc research. This book will help you learn how to choose a model for your problem, how to evaluate the performance of your models, and how you can use C# to build machine learning models for your future projects.

You will get an overview of the machine learning systems and how you, as a C# and .NET developer, can apply your existing knowledge to the wide gamut of intelligent applications, all through a project-based approach. You will start by setting up your C# environment for machine learning with the required packages, Accord.NET, LiveCharts, and Deedle. We will then take you right from building classifcation models for spam email fltering and applying NLP techniques to Twitter sentiment analysis, to time-series and regression analysis for forecasting foreign exchange rates and house prices, as well as drawing insights on customer segments in e-commerce. You will then build a recommendation model for music genre recommendation and an image recognition model for handwritten digits. Lastly, you will learn how to detect anomalies in network and credit card transaction data for cyber attack and credit card fraud detections

What you will learn:
Set up C# environment for machine learning with required packages
Essential steps to build classification models for spam email filtering
Feature engineering using NLP techniques for Twitter sentiment analysis
Forecast foreign exchange rates using continuous and time-series data
Building a recommendation model for Music Genre Recommendation
Data munging image dataset for handwritten digit recognition
Choosing the right confidence threshold for cyber attack detection
One-Class Support Vector Machine for credit card fraud detection

Who This Book Is For:
This book is for C# & .NET developers who have strong knowledge of C#, then this book is perfect for you to get machine learning into your real-world projects and make the application much smarter