This is a repository for the 5-day program for Machine Learning with Python at Daegu Il Science High School in January 2025. This program is designed for approaching machine learning through hands-on practices and team projects.
This 5-day machine learning course is designed to introduce students to the field of machine learning with hands-on projects. Through a combination of lectures, coding exercises, and group projects, students will develop a theoretical understanding of machine learning fundamentals and practical skills in implementing models. The course begins with an overview of Python programming and key statistical concepts essential for machine learning. Students will explore topics such as data preprocessing, feature engineering, algorithm selection, and model training, and will apply these concepts to real-world datasets. Advanced topics like hyperparameter tuning, model evaluation, and interpretability will also be introduced. By the end of the course, students will have a clear understanding of the complete machine learning workflow. The course will also cover ethical considerations and best practices in machine learning. Students will learn to critically evaluate the implications of their models, ensuring they use machine learning responsibly and effectively. The course culminates in a collaborative group project where students tackle a real-world problem, applying their skills to design, train, and evaluate machine learning models.
By the end of this course, students should be able to:
- Gain Proficiency in Python for Data Science and Machine Learning:
- Master basic Python syntax, variables, and data types.
- Utilize Python libraries like NumPy, pandas for data manipulation, and Matplotlib, Seaborn for data visualization.
- Learn Fundamental Machine Learning Concepts:
- Understand different types of machine learning: supervised, unsupervised, and reinforcement learning.
- Get acquainted with basic machine learning algorithms and their practical applications.
- Develop Skills in Exploratory Data Analysis (EDA)
- Acquire Knowledge in Model Selection and Tuning
- Introduction to Neural Networks and Deep Learning
Anaconda is a useful package management software that allows you to run Python and Jupyter notebooks very easily. Installing Anaconda is the easiest way to make sure you have all the necessary software to run the materials for this workshop. Complete the following steps:
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Download and install Anaconda (Python 3.9 distribution). Click "Download" and then click 64-bit "Graphical Installer" for your current operating system.
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Download the Python-Machine-Learning workshop materials:
- Click the green "Code" button
- Click "Download Zip".
- Extract this file to a folder on your computer
Some of the materials are adapted from UC Berkeley's D-Lab workshops!