Email the Author
You can use this page to email Fiodar Sazanavets about Machine Learning for C# Developers Made Easy.
About the Book
Create production quality machine learning models in C# without leaving the .NET ecosystem.
Machine Learning for C# Developers teaches you how to build powerful machine learning (ML) models using your C# and .NET skills—no Python required! You’ll learn how to use the innovative ML.NET framework to build a virtual assistant that can recognize objects, classify software errors, estimate salaries from a job description, and more.
In Machine Learning for C# Developers you’ll learn:
- Machine learning fundamentals
- Supervised, unsupervised, and reinforced model training
- Build and train models with C# code
- Automating the machine learning process
Machine learning is a powerful tool for forecasting trends, modeling customer behaviors, and identifying other important patterns in your data that will help you make more informed decisions. Recent advances in deep learning make it possible to build powerful ML-driven tools that can do everything from personalized product recommendations to image recognition, to text and code generation. For data scientists and developers, powerful frameworks like ML.NET and automated machine learning (AutoML) systems can greatly enhance your productivity in building, training, and deploying even the most advanced ML models.
About the Author
I am a senior software engineer working for Microsoft. I have over a decade of professional experience and am a past recipient of the Microsoft MVP award. I primarily specialize in .NET and Microsoft stack. I am enthusiastic about creating well-crafted software that fully meets business needs.
Throughout my career, I have successfully developed software of various types and various levels of complexity in multiple industries. This includes a passenger information management system for a railway, distributed smart clusters of IoT devices, e-commerce systems, financial transaction processing systems, and more. I have also successfully led and mentored teams of software developers.
I enjoy sharing my knowledge with the community. This motivates me to mentor aspiring developers and create educational content, which includes blog posts, technical books, and online courses. I regularly write about software development on my personal website, scientificprogrammer.net.