Machine Learning, Imperial College London 2017

A two-weeks in-depth course of machine learning organized by Yandex Data School at Imperial College. Contains theory and much practice!

Main topics:

Challenges

There were two challenges during the course:

Name		Name	Last commit message	Last commit date
Latest commit History 41 Commits
Lectures		Lectures
data		data
img		img
.gitignore		.gitignore
0-intro-to-python.ipynb		0-intro-to-python.ipynb
1.1-introduction-to-numpy.ipynb		1.1-introduction-to-numpy.ipynb
1.2-introduction-to-sklearn.ipynb		1.2-introduction-to-sklearn.ipynb
2-introduction-to-pandas-matplotlib-and-regression.ipynb		2-introduction-to-pandas-matplotlib-and-regression.ipynb
3.1-sparse.ipynb		3.1-sparse.ipynb
3.2-linear-models-and-trees.ipynb		3.2-linear-models-and-trees.ipynb
4-ensembling.ipynb		4-ensembling.ipynb
5.1-theano-and-neural-networks.ipynb		5.1-theano-and-neural-networks.ipynb
5.2-Keras-and-digits.ipynb		5.2-Keras-and-digits.ipynb
6-Reweighting-Flatness.pdf		6-Reweighting-Flatness.pdf
6-reweighting.ipynb		6-reweighting.ipynb
7-Deep Learning.pdf		7-Deep Learning.pdf
Dockerfile		Dockerfile
README.md		README.md
theoretical task 1.pdf		theoretical task 1.pdf
theoretical task 2.pdf		theoretical task 2.pdf
utils.py		utils.py