“Most developers these days have heard of machine learning, but when trying to find an ‘easy’ way into this technique, most people find themselves getting scared off by the abstractness of the concept of Machine Learning and terms as regression, unsupervised learning, Probability Density Function and many other definitions. If one switches to books there are books such as An Introduction to Statistical Learning with Applications in R and Machine Learning for Hackers who use programming language R for their examples.
The first section ‘The global idea of machine learning’ contains all important concepts and notions you need to know about to get started with the practical examples that are described in the section ‘Practical Examples’. The section practical examples is inspired by the examples from the book Machine Learning for Hackers. Additionally the book Machine Learning in Action was used for validation purposes.
Note that in this blog, ‘new’ definitions are hyperlinked such that if you want, you can read more regarding that specific topic, but you are not obliged to do this in order to be able to work through the examples.
As final note I’d like to thank the following people:
- Haifeng Li for his support and writing the awesome and free to use library Smile.
- Erik Meijer for all suggestions and supervision of the process of writing this blog.
- Richard van Heest for his feedback and co-reading the blog.
- Lars Willems for his feedback and co-reading the blog…”