Computer Science 189
Title | Introduction to Machine Learning |
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Units | 4 |
Description | Theoretical foundations, algorithms, methodologies, and applications for machine learning. Topics may include supervised methods for regression and classication (linear models, trees, neural networks, ensemble methods, instance-based methods); generative and discriminative probabilistic models; Bayesian parametric learning; density estimation and clustering; Bayesian networks; time series models; dimensionality reduction; programming projects covering a variety of real-world applications. |
Course Guide | Course Guide |
Sections | Instructor | Teaching Effectiveness | How worthwhile was this course? |
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Fall 2023 | Jennifer Listgarten | ||
Jitendra Malik | |||
Spring 2023 | Jonathan Shewchuk | ||
Fall 2022 | Jennifer Listgarten | ||
Jitendra Malik | |||
Spring 2022 | Marvin Zhang | ||
Spring 2022 | Jonathan Shewchuk | ||
Fall 2021 | Jennifer Listgarten | ||
Jitendra Malik | |||
Spring 2021 | Jonathan Shewchuk | ||
Fall 2020 | Jennifer Listgarten | ||
Jitendra Malik | |||
Anant Sahai | |||
Spring 2020 | Jonathan Shewchuk | ||
Fall 2019 | Jennifer Listgarten | ||
Stella Yu | |||
Fall 2018 | Moritz Hardt | ||
Ben Recht | |||
Stella Yu | |||
Summer 2018 | Ke Li | ||
Joshua P Tobin | |||
Spring 2018 | Jennifer Listgarten | ||
Anant Sahai | |||
Fall 2017 | Anant Sahai | ||
Stella Yu | |||
Spring 2017 | Jonathan Shewchuk | ||
Fall 2016 | Jitendra Malik | ||
Ben Recht | |||
Spring 2016 | Jonathan Shewchuk | ||
Fall 2015 | Alexei Efros | ||
Isabelle Guyon | |||
Spring 2015 | Peter Bartlett | ||
Alexei Efros | |||
Spring 2014 | Alexei Efros | ||
Jitendra Malik | |||
Spring 2013 | Jitendra Malik | ||
Fall 1990 | Lotfi A. Zadeh | ||
Fall 1989 | Lotfi A. Zadeh | ||
Fall 1988 | Lotfi A. Zadeh | ||
Overall Rating | Teaching Effectiveness | How worthwhile was this course? | |