CMSC643: Machine Learning and Data Mining - Calendar

Date	Title	Additional Prep	Work Due
8/28	Course Introduction An example ML application (HTML) An example ML application (IPython Notebook)
9/4	Finding Similar Items / Itemset Mining	MMD, Ch. 3 and 6
9/11	Mathematical Background; Perceptrons	CIML 3 and 4
9/18	Linear Models	CIML 7
9/25	Practial Issues: Feature Construction Kernel Methods	CIML 5.1-5.4 CIML 11
10/2	Practical Issues; Model Selection and Assessment	CIML 5	Gradient Descent Exercise
10/9	Decision Trees	CIML 1; 13
10/16	Project 2 review Random Forests	CIML 13
10/23	Ensemble Methods	CIML 13
10/30	Unsupervised Learning: Clustering Unsupervised Learning: Dimensionality Reduction	CIML Ch. 15, 16
11/6	Neural Networks
11/13	Deep Learning Recurrent Neural Nets (from Stanford group) Intro to Keras (.ipynb) Intro to Keras (.html)	Deep Learning Book, Ch. 6
11/20	Bias and Fairness	CIML Ch. 8
11/27	Efficient Learning; Large-Scale Machine Learning	CIML Ch. 14
12/4	Oral Examinations