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start [2025/02/22 15:56]
ge461 [Textbooks] |
start [2025/03/23 16:50] (current)
ge461 |
| ** Data collection; storage; querying; SQL, NoSQL; cloud; distributed storage and computing. ** [Körpeoğlu] \\ | ** Data collection; storage; querying; SQL, NoSQL; cloud; distributed storage and computing. ** [Körpeoğlu] \\ |
| Topic Details: RDMBs, SQL; SQLite, Pandas; NoSQL; MapReduce and Hadoop; Spark.\\ | Topic Details: RDMBs, SQL; SQLite, Pandas; NoSQL; MapReduce and Hadoop; Spark.\\ |
| Slides and Additional Material:{{:slides.pdf | Slides.pdf}}\\ | Slides and Additional Material:{{:slides.pdf | data_storage_and_access.pdf}}\\ |
| Project/Exercise-Problem-Set/Homework: None this week.\\ | Project/Exercise-Problem-Set/Homework: None this week.\\ |
| References: | References: |
| ==== Week 5 (Feb 24, Feb 27) ==== | ==== Week 5 (Feb 24, Feb 27) ==== |
| **Basic models; parametric models; fitting. ** [Arıkan] \\ | **Basic models; parametric models; fitting. ** [Arıkan] \\ |
| Topic Details: Regression\\ | Topic Details: Multiparameter Linear Regression\\ |
| Slides and Additional Material:\\ | Slides and Additional Material: {{ :ch3_linear_regression.pdf |}} \\ |
| Project/Exercise-Problem-Set/Homework:\\ | Project: Solve following questions using Linear Regression: Exercises 3.7.8 and 3.7.9 in the ISLR Reference Book given below \\ |
| References:\\ | References: An Introduction to Statistical Learning with Applications in Python, R, Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani and Jonathon Taylor. \\ |
| Events: \\ | Events: \\ |
| |
| ==== Week 6 (Mar 3, Mar 6) ==== | ==== Week 6 (Mar 3, Mar 6) ==== |
| ** Application ** [Arıkan] \\ | ** Application ** [Arıkan] \\ |
| Topic Details:\\ | Topic Details: Model Selection in Multiparameter Regression \\ |
| Slides:\\ | Slides: {{ :Ch6_Model_Selection.pdf |}}\\ |
| Project/Exercise-Problem-Set/Homework:\\ | Project/Exercise-Problem-Set/Homework: None this week\\ |
| References:\\ | References: An Introduction to Statistical Learning with Applications in Python, R, Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani and Jonathon Taylor. \\ |
| Events: \\ | Events: \\ |
| |
| ** Dimensionality reduction; visualization.** [Aksoy] \\ | ** Dimensionality reduction; visualization.** [Aksoy] \\ |
| Topic Details: Feature reduction, feature selection, high-dimensional data visualization.\\ | Topic Details: Feature reduction, feature selection, high-dimensional data visualization.\\ |
| Slides and Additional Material:\\ | Slides and Additional Material: {{ :ge461_dimensionality.pdf |Dimensionality slides}}, {{ :knaw_t-sne_talk.pptx |t-SNE slides}}\\ |
| Project/Exercise-Problem-Set/Homework:\\ | 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]]\\ |
| ** Unsupervised learning, clustering. ** [Aksoy] \\ | ** Unsupervised learning, clustering. ** [Aksoy] \\ |
| Topic Details: K-means clustering, mixture models, hierarchical clustering.\\ | Topic Details: K-means clustering, mixture models, hierarchical clustering.\\ |
| Slides and Additional Material:\\ | Slides and Additional Material: {{ :ge461_clustering.pdf |Clustering slides}}\\ |
| Project/Exercise-Problem-Set/Homework: \\ | Project/Exercise-Problem-Set/Homework: \\ |
| References: [[https://www.mathworks.com/help/stats/cluster-analysis.html|Matlab: cluster analysis]], [[https://scikit-learn.org/stable/modules/clustering.html|Scikit-learn: clustering]], [[https://scikit-learn.org/stable/auto_examples/index.html#clustering|Scikit-learn: clustering examples]]\\ | References: [[https://www.mathworks.com/help/stats/cluster-analysis.html|Matlab: cluster analysis]], [[https://scikit-learn.org/stable/modules/clustering.html|Scikit-learn: clustering]], [[https://scikit-learn.org/stable/auto_examples/index.html#clustering|Scikit-learn: clustering examples]]\\ |
| ** 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:\\ | Slides and Additional Material: {{ ::ge461_ml_in_healthcare.pdf |}} \\ |
| Project/Exercise-Problem-Set/Homework:\\ | 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)\\ |
| ** Data mining; online data stream classification; applications.** [Can] \\ | ** Data mining; online data stream classification; applications.** [Can] \\ |
| Topic Details: Concept drift, ensemble-based classification, text mining. \\ | Topic Details: Concept drift, ensemble-based classification, text mining. \\ |
| Slides and Additional Material:\\ | Slides and Additional Material: {{ :ge461_datastreamminingspring25.pdf |}}\\ |
| | Project Tentative Days: Announcement **April 28** or earlier, Due date: **May 18, 23:59.** \\ |
| Project/Exercise-Problem-Set/Homework:\\ | Project/Exercise-Problem-Set/Homework:\\ |
| References: \\ | References: \\ |
| * [[https://www.cs.ubc.ca/~murphyk/MLbook/|Machine Learning: a Probabilistic Perspective]] | * [[https://www.cs.ubc.ca/~murphyk/MLbook/|Machine Learning: a Probabilistic Perspective]] |
| * [[https://www-bcf.usc.edu/~gareth/ISL/|An Introduction to Statistical Learning, R, Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani.]] | * [[https://www-bcf.usc.edu/~gareth/ISL/|An Introduction to Statistical Learning, R, Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani.]] |
| * [[https://hastie.su.domains/ISLP/ISLP_website.pdf.download.html|An Introduction to Statistical Learning with Applications in Python, R, Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshiraniand Jonathon Taylor.]] | * [[https://hastie.su.domains/ISLP/ISLP_website.pdf.download.html|An Introduction to Statistical Learning with Applications in Python, R, Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani and Jonathon Taylor.]] |
| * [[https://www.springer.com/gp/book/9780387310732|Pattern Recognition and Machine Learning, Christopher Bishop]] | * [[https://www.springer.com/gp/book/9780387310732|Pattern Recognition and Machine Learning, Christopher Bishop]] |
| * [[https://www.amazon.com/Neural-Networks-Learning-Machines-3rd/dp/0131471392|Neural Networks and Learning Machines]] | * [[https://www.amazon.com/Neural-Networks-Learning-Machines-3rd/dp/0131471392|Neural Networks and Learning Machines]] |
