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start [2025/03/20 12:53]
ge461 [Week 13 (Apr 21, Apr 24)] |
start [2025/03/23 16:50] (current)
ge461 |
| Topic Details: Feature reduction, feature selection, high-dimensional data visualization.\\ | Topic Details: Feature reduction, feature selection, high-dimensional data visualization.\\ |
| Slides and Additional Material: {{ :ge461_dimensionality.pdf |Dimensionality slides}}, {{ :knaw_t-sne_talk.pptx |t-SNE slides}}\\ | Slides and Additional Material: {{ :ge461_dimensionality.pdf |Dimensionality slides}}, {{ :knaw_t-sne_talk.pptx |t-SNE slides}}\\ |
| Project/Exercise-Problem-Set/Homework: (tentative dates: assigned March 24, 2025, due 23:59 on April 7, 2025)\\ | Project/Exercise-Problem-Set/Homework: [{{ :ge461_project_dimensionality.pdf |Project}} ({{ :fashion_mnist.zip |data}})] (due 23:59 on April 7, 2025)\\ |
| References: [[https://www.mathworks.com/help/stats/dimensionality-reduction.html|Matlab: dimensionality reduction]], [[https://scikit-learn.org/stable/modules/decomposition.html|Scikit-learn: decomposition]], [[https://scikit-learn.org/stable/auto_examples/index.html#decomposition|Scikit-learn: decomposition examples]], [[https://scikit-learn.org/stable/modules/manifold.html|Scikit-learn: manifold learning]], [[https://www.mathworks.com/discovery/data-visualization.html|Matlab: data visualization]], | References: [[https://www.mathworks.com/help/stats/dimensionality-reduction.html|Matlab: dimensionality reduction]], [[https://scikit-learn.org/stable/modules/decomposition.html|Scikit-learn: decomposition]], [[https://scikit-learn.org/stable/auto_examples/index.html#decomposition|Scikit-learn: decomposition examples]], [[https://scikit-learn.org/stable/modules/manifold.html|Scikit-learn: manifold learning]], [[https://www.mathworks.com/discovery/data-visualization.html|Matlab: data visualization]], |
| [[https://matplotlib.org/|Matplotlib: data visualization]], [[https://lvdmaaten.github.io/tsne/|t-SNE]]\\ | [[https://matplotlib.org/|Matplotlib: data visualization]], [[https://lvdmaaten.github.io/tsne/|t-SNE]]\\ |
| ** Machine learning in healthcare. ** [Çukur] \\ | ** Machine learning in healthcare. ** [Çukur] \\ |
| Topic Details: Healthcare analytics: diagnostics, medical imaging, in-patient care, hospital management, risk analytics, wearables. Deep learning architectures for medical applications; \\ | Topic Details: Healthcare analytics: diagnostics, medical imaging, in-patient care, hospital management, risk analytics, wearables. Deep learning architectures for medical applications; \\ |
| Slides and Additional Material:\\ {{ ::ge461_ml_in_healthcare.pdf |}} | Slides and Additional Material: {{ ::ge461_ml_in_healthcare.pdf |}} \\ |
| Project/Exercise-Problem-Set/Homework:\\ {{ ::ge461_pw13_description.pdf |}}; {{ ::ge461_pw13_data.zip |}} (due date: 11 May 2025, 17:00) | Project/Exercise-Problem-Set/Homework: {{ ::ge461_pw13_description.pdf |}}; {{ ::ge461_pw13_data.zip |}} (due date: 11 May 2025, 17:00)\\ |
| References: Hastie, Tibshirani and Friedman, The Elements of Statistical Learning, Ch. 11 and 14; Mead, Analog VLSI and Neural Systems, Ch. 4; Bishop, Pattern Recognition and Machine Learning, Ch. 5\\ | References: Hastie, Tibshirani and Friedman, The Elements of Statistical Learning, Ch. 11 and 14; Mead, Analog VLSI and Neural Systems, Ch. 4; Bishop, Pattern Recognition and Machine Learning, Ch. 5\\ |
| Events: National Sovereignty and Children's Day (Apr 23)\\ | Events: National Sovereignty and Children's Day (Apr 23)\\ |
