Understanding the upsides and downsides.
...with an analogy.
A cool Jupyter hack.
A quick pros and cons summary of PCA.
Loss functions of common ML algorithms depicted in a single frame.
If not, when is it not needed?
Quick data labelling from the comfort of Jupyter.
An unexplored direction of visualising a confusion matrix.
...with advantages and disadvantages.
Thinking from a scope perspective.
Not all datasets are linearly separable.
Most common magic methods in Python summarised in a single frame.
