Mathias Brandewinder: Math and Machine Learning using .NET - Episode 208
In this episode, Mathias Brandewinder shares his passion for solving complex business problems using software engineering and mathematics. He discusses how he got into programming through his love for math and his current focus on functional programming with F#, machine learning, and data science. Mathias also talks about his favorite charting component for .NET and the inspiration behind writing his book, "Machine Learning Projects for .NET Developers."
Throughout the podcast, Mathias touches on various topics, including the benefits of F# over C#, the challenges of computer-based mathematics, and exciting math-related libraries such as DiffSharp and Math.Net Numerics. He also emphasizes that math can be genuinely fun, contrary to popular belief!
If you're interested in learning more about the intersection of math and machine learning with .NET, this podcast is definitely worth a listen. Mathias provides valuable insights and resources that can help you enhance your understanding and ability to apply mathematical concepts in software engineering.
The post Mathias Brandewinder: Math and Machine Learning using .NET - Episode 208 originally appeared on Azure DevOps Podcast.
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Learn moreThe Azure DevOps Podcast is a show for developers and devops professionals shipping software using Microsoft technologies. Each show brings you hard-hitting interviews with industry experts innovating better methods and sharing success stories. Listen in to learn how to increase quality, ship quickly, and operate well. Hosted by Jeffrey Palermo and sponsored by Clear Measure, Inc.
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