Python for Machine Learning (ML) Course

Course instructor:

Fabio Mardero is an Italian data scientist. He is a graduate in physics and in statistical and actuarial sciences. He is currently working for a well-known Italian insurance company as a data scientist and assessor of non-life technical provisions.

Course overview and lectures

Duration: 14+ hours

Project

Insurance project

Italian COVID dataset (official data): https://github.com/pcm-dpc/COVID-19

Insurance Dataset: https://www.kaggle.com/anmolkumar/health-insurance-cross-sell-prediction

1. Introduction to Python

Programming language features, VS Code, Jupyter Notebook/Lab (Colab), virtual environments, variables, data types, lists and dictionaries.

Course 1: Overview

Course 2: Configure the Python project

Course 3: Venv (virtual environment)

Lecture 4: Cottage

Lecture 5: Python and IDE tools

Lecture 6: Data Types

2. If/else and loops

If/else, loops, iterators and generators, error handling.

Lecture 7: Loops & If Else

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3. Functions and classes

Functions, decorators, classes, inheritance, decorators inside classes.

Lecture 8: Class function

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4. Pandas and Numpy

Tables and matrices, file reading, DataFrame, Series, pivot tables, group by, pipelines, datetime objects.

Lecture 9: Pandas Part 1

Conference 10: Pandas Part 2

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5. Static plot

Static plots using matplotlib and seaborn libraries.

Lecture 11: Static plot

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6. Dynamic plot

Animations, dynamic plots using the altair library

Lecture 12: Dynamic plot

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seven. Unit testing and logging

Arranging files to build a Python library, assertions, test cases (unittest library), logging (logging library)

Lecture 13: Unit tests

Lecture 14: Registration

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8. Computer Vision

PIL, OpenCV

Lecture 15: computer vision

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