This page contains an outline of the topics, content, and assignments for the semester.
Note that this schedule will be updated as the semester progresses, with all changes documented here.
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Jan. 7 |
Overview |
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Jan. 10 |
Essential Celluar Biology |
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2 |
Jan. 14 |
Essential Celluar Biology (continued) |
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Jan. 17 |
Essential Celluar Biology (continued) |
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3 |
Jan. 21 |
Essential Bioinformatis skills |
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Jan. 24 |
Fundamentals of machine learning |
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Jan. 28 |
Fundamentals of machine learning |
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Jan. 31 |
Fundamentals of machine learning |
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Feb. 4 |
Fundamentals of machine learning |
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Feb. 7 |
Unsupervised learning |
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Feb. 11 |
Regularized linear models |
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Feb. 14 |
Decision Trees |
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Feb. 18 |
Reading week |
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Feb. 21 |
Reading week |
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Feb. 25 |
Midterm examination |
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Feb. 28 |
Hidden Markov Models |
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Mar. 4 |
Support Vector Machines |
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Mar. 7 |
Kernel Methods |
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Mar. 11 |
Deep Learning Fundamentals |
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Mar. 14 |
Deep Learning Embeddings and Transfer Learning |
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Mar. 18 |
Deep Learning Architecture |
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Mar. 21 |
Deep Learning Practical Considerations |
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Mar. 25 |
Rule Learning |
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Mar. 28 |
Graph Learning |
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Apr. 1 |
Ensemble Learning |
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Apr. 4 |
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