Level: Intermediate to Advanced
This hands-on workshop will teach you how to create traditional non-neural machine learning prediction systems. You will learn what six fundamental ML techniques are and what types of problems they can (and cannot) solve, implementing them using only raw C# without any external libraries.
This workshop emphasizes practical techniques, but also gives you just enough theory so you can modify and customize your systems.
Techniques covered include: logistic regression binary classification, naive Bayes multiclass classification, k-nearest neighbors classification, Thompson Sampling and epsilon-greedy bandit algorithms, and k-means clustering.
You will learn:
- What types of problems machine learning can and cannot solve
- How to implement the six fundamental ML techniques using C#
- How to interpret the results of an machine learning model