Unlock the potential of machine learning with our "Foundations of Machine Learning with Python" course, designed for beginners eager to delve into the world of intelligent data analysis using Python and Quarto. This hands-on class introduces participants to the fundamental concepts and practical skills required to implement machine learning algorithms using Python. Whether you're a data enthusiast, analyst, or professional looking to enhance your skill set, this course provides a solid introduction to the essentials.
This class provides a solid foundation in using Scikit-Learn, the versatile machine learning library in Python. Whether you're a data enthusiast, analyst, or aspiring data scientist, this course equips you with the essential skills to implement machine learning models for classification, regression, and clustering.
Unlock the potential of machine learning with our "Foundations of Machine Learning with Python" course, designed for beginners eager to delve into the world of intelligent data analysis using Python and Quarto. This hands-on class introduces participants to the fundamental concepts and practical skills required to implement machine learning algorithms using Python. Whether you're a data enthusiast, analyze, or professional looking to enhance your skill set, this course provides a solid introduction to the essentials.
This class provides a solid foundation in using Scikit-Learn, the versatile machine learning library in Python. Whether you're a data enthusiast, analyze, or aspiring data scientist, this course equips you with the essential skills to implement machine learning models for classification , regression, and clustering.
Textbooks
Paper, D. (2020). Hands-on Scikit-Learn for Machine Learning Applications: Data Science Fundamentals with Python. Apress. Download from the University Library for free. https://doi.org/10.1007/978-1-4842-5373-1
References
McKinney, Wes. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. Second edition, O'Reilly Media, Inc, 2018.
Grus, Joel. Data Science from Scratch: First Principles with Python. Second edition, O'Reilly Media, 2019.
Textbooks
Paper, D. (2020). Hands-on Scikit-Learn for Machine Learning Applications: Data Science Fundamentals with Python. Apress. Download from the University Library for free. https://doi.org/10.1007/978-1-4842 -5373-1
References
McKinney, Wes. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. Second edition, O'Reilly Media, Inc, 2018.
Grus, Joel. Data Science from Scratch: First Principles with Python. Second edition, O'Reilly Media, 2019.
| 評分項目 Grading Method | 配分比例 Grading percentage | 說明 Description |
|---|---|---|
| Attendance and class participation Attendance and class participation attendance and class participation |
30 | Students are required to attend class |
| AssignmentsAssignments Assignments |
30 | |
| Final exam/presentationFinal exam/presentation final exam/presentation |
40 |
