This repo contains all of the source code files in jupyter notebook format for my blog on machine learning.
- http://mlhq.io/blogs/important-statistics
- http://mlhq.io/blogs/dataset-shape-and-spread
- http://mlhq.io/blogs/linear-regression
- http://mlhq.io/blogs/linear-regression-theory
- http://mlhq.io/blogs/multivariate-linear-regression-theory
- http://mlhq.io/blogs/multivariate-linear-regression-python
- http://mlhq.io/blogs/logistic-regression-python
- http://mlhq.io/blogs/logistic-regression-theory
- http://mlhq.io/blogs/ridge-regression-theory
- http://mlhq.io/blogs/k-means-clustering-theory
What is the path to being a machine learning engineer.
Basics:
Metrics, basic - False positive, False negative
Effect of imbalanced datasets, how to tune for aggressiveness
What kind of data do I have, what kind of algorithm do I need
Classification vs Regression
Time series data (order matters)
Markovian space, non-markovian
How do I guess and check effectively
How do I deal with roadblocks efficiently