Skoltech ML course, 2020

Some implemented features that may become useful later:

Homeworks

• HW2, part1:

  • plotting with customizable layout (HW2, part1), plt.GridSpec from matplotlib.pyplot
  • highlighting cells of pd.DataFrame object, .style.apply(color_fn)
  • example of two aligned horizontal barplots with adjusted tick labels

• HW2, part2:

  • theory problems

• HW3, part1:

  • nothing

• HW3, part2:

  • a bit of theory, just a smattering

There were 4 homeworks; HW1 and HW4 contained nothing useful, so I didn't upload them

Project

See the project description in the project folder

• Exponentially dilated causal convolutions
• Recurrent and convolutional encoder for time series
• Recurrent and convolutional decoder for time series
• Convolutional classifier for time series
• Convolutional Regressor for time series reconstruction from persistence landscapes
• Oversampling technique (implemented in PyTorch)
• Some other tools