Python for Machine Learning (ML) Course
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
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
3. Functions and classes
Functions, decorators, classes, inheritance, decorators inside classes.
Lecture 8: Class function
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
5. Static plot
Static plots using matplotlib and seaborn libraries.
Lecture 11: Static plot
6. Dynamic plot
Animations, dynamic plots using the altair library
Lecture 12: Dynamic plot
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
8. Computer Vision
Lecture 15: computer vision