As readers of my blog will know, I want to learn more about machine learning. I’ve managed to run some samples, and I’ve built my own first little samples. It feels like the next step is to understand more about the different algorithms, for example when to pick which one and how to tune the parameters to achieve the best results.
To learn more, I’ve started to watch the first hours of the awesome courses below. The courses are a great introduction to machine learning and very different from most other videos I found which often seem to assume you are already a data scientist.
The courses are free courses provided by Udacity. The speakers are phenomenal, the content is very interesting and easy to understand.
To run the exercises in the courses via Scikit Learn on Bluemix you can follow the documentation in this article.
Intro to Machine Learning: Pattern Recognition for Fun and Profit
Machine Learning: Supervised, Unsupervised & Reinforcement
Machine Learning Courses:
- Intro to Machine Learning
- Machine Learning:Supervised Learning Part 1a of 3
- Machine Learning – Supervised Learning Part 1b of 3
- Machine Learning:Unsupervised Learning Part 2 of 3
- Machine Learning:Reinforcement Learning – Part 3 of 3
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