Finished Machine Learning Course
I had couple of ML-related courses at University and used it in practice, but, still it was very interesting to review and refresh the core concepts.
Especially from such a badass ML expert as Andrew Ng, with lots of practical examples and advices.
- Supervised / Unsupervised Learning.
- Linear Regression, Logistic Regression, SVM.
- Neural Networks.
- K-means, PCA, Anomaly Detection.
- Recommending Systems, Collaborative Filtering.
- Bias / Variance, Regularization, Precision / Recall, Learning Curve etc.
- How to gather, amplify and generate Learning Data.
- Large-scale Learning, Stochastic Gradient, Map/Reduce etc.
Also learn core topics about NLP - Natural Language Processing: TF/IDF, String Similarity, etc.
And, refreshed my rusty memory of Linear Algebra and Statistics from University.
Really like that course, lots of examples how to apply those technics to real cases.