581SM - STATISTICAL MACHINE LEARNING 2018
Schema della sezione
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This is the moodle page of the Statistical Machine Learning of the Master Program in Data Science and Scientific Computing. Here you will find the material of the course, including slides, videos, textbooks, the lab assignments, and the instructions for the final project.
Lectures.
Wednesday 09.30-13.00
Thursday 11.00-13.00 and 14.00-16.00
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Textbooks containing the material treated in the course (and much more). In pdf, for your private use. Do not distribute.
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Here you can find useful links and other material to read.
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Here you can find several datasets to experiment with.
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Here you can find several datasets to experiment with classification techniques.
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Pandas is the main library to manipulate and explore datasets in Python. Here you will find Jupyter Notebooks tutorials and links to tutorials to learn Pandas. We will also cover some fundamentals of data visualization in matplotlib and seaborne.
Before playing with Pandas, make sure you install Python 3. My suggestion is that you install the ANACONDA distribution - it has almost all the libraries needed already installed. You will need Jupyter Notebook. A good idea is to install also an IDE, like PyCharm CE.
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Introduction to Bayesian statistics, and Bayesian linear regression and classification.
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