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Master the art of machine learning with .NET and gain an insight into real-world applications. Includes ASP.NET Core 1.0 About This Book* Based on .NET framework 4.6.1, includes examples on ASP .NET 5.0* Set up your business application to start using machine learning techniques* Familiarize the user with some of the more common .NET libraries for machine learning* Implement several common machine learning techniques* Evaluate, optimize and adjust machine learning modelsWho This Book Is For This book is targeted at .Net developers who want to build complex machine learning systems. Some basic understanding of data science is required. What You Will Learn* Set up your business application to start using machine learning* Accurately predict the future using regressions* Discover hidden patterns using decision trees* Acquire, prepare, and combine datasets to drive insights* Optimize business throughput using Bayes Classifier* Discover (more) hidden patterns using KNN and Naive Bayes* Discover (even more) hidden patterns using K-Means and PCA* Use Neural Networks to improve business decision making while using the latest ASP.N ET technologies* Explore "Big Data", distributed computing, and how to deploy machine learning models to IoT devices - making machines self-learning and adapting* Along the way, learn about Open Data, Bing maps, and MBraceIn Detail .Net is one of the widely used platforms for developing applications. With the meteoric rise of Machine learning, developers are now keen on finding out how can they make their .Net applications smarter. Also, .NET developers are interested into moving into the world of devices and how to apply machine learning techniques to, well, machines. This book is packed with real-world examples to easily use machine learning techniques in your business applications. You will begin with introduction to F# and prepare yourselves for machine learning using .NET framework. You will be writing a simple linear regression model using an example which predicts sales of a product. Forming a base with the regression model, you will start using machine learning libraries available in .NET framework such as Math.NET, Numl.NET and Accord.NET with the help of a sample application. You will then move on to writing multiple linear regressions and logistic regressions. You will learn what is open data and the awesomeness of type providers. Next, you are going to address some of the issues that we have been glossing over so far and take a deep dive into obtaining, cleaning, and organizing our data. You will compare the utility of building a KNN and Naive Bayes model to achieve best possible results. Implementation of Kmeans and PCA using Accord.NET and Numl.NET libraries is covered with the help of an example application. We will then look at many of issues confronting creating real-world machine learning models like overfitting and how to combat them using confusion matrixes, scaling, normalization, and feature selection. You will now enter into the world of Neural Networks and move your line of business application to a hybrid scientific application. After you have covered all the above machine learning models, you will see how to deal with very large datasets using MBrace and how to deploy machine learning models to Internet of Thing (IoT) devices so that the machine can learn and adapt on the fly.

Once the mighty fortress had stood strong, defended by the mightiest of all Drenai heroes, Druss, the Legend. But now a tyrannical, mad emperor had Mastering .NET Machine Learning download book seized control of the fortress, and his twisted will was carried throughout the land by the Joinings --- abominations that were half-man, half-beast. Tenaka Khan was a half-breed himself, hated by the Drenai for his Nadir blood and despised by the Nadir for his Drenai ancestry. But he alone had a plan to destroy the emperor. The last heroes of the Drenai joined with him in a desperate gamble to bring down the emperor -- even at the cost of their own destruction. (Musicians Institute Press). Explore the chords, rhythms, and techniques used by the greatest funk keyboardists! Subjects covered include: common chords and progressions; classic funk rhythms, licks and patterns; synth bass & multiple keyboard playing; and pitch wheel and modulation. The accompanying CD includes 81 full-band tracks.

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Author: Jamie Dixon
Number of Pages: 460 pages
Published Date: 28 Mar 2016
Publisher: Packt Publishing Limited
Publication Country: Birmingham, United Kingdom
Language: English
ISBN: 9781785888403
Download Link: Click Here
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