Machine Learning (11) - Machine Learning Algorithms: Explained!
One question that always pops up in any machine learning problem: Which algorithm should I use? What do the algorithms do anyways? After briefly going over a typical machine learning process, we have a closer look at third step, i.e. building the model: What algorithms are out there? Which one should we use? One of Microsoft's Data Scientist, Brandon Rohrer, has written a nice three-part blog series on introducing data science with no jargon: Furthermore, there is one really neat cheat sheet created by Microsoft's Data Science team on when to use which algorithm: Finally, one last resource that I hihgly recommend: Top 10 data mining algorithms in plain English.
Mar-9-2017, 10:55:17 GMT