Description
WEEK #1
1 What ML.
2) Introducin
3) Qw2 #1
4) Other materials
5) Model and Cost Fixn
6) Paramts Learning
9) Review fruit
8) Linear Algebra review
9) Review Quiz
WEEK #4
1) Motivatns
2)NN
3) Applicatns
4) Review (Qui2+PA)
WEEK #7
1) Large Mougin Class’n.
2) Kernels
3) EVM’s in Practice
4) Review (QU12+ P.Α.)
WEEK #2
1) Environment Setup Instr
WEEK #3
1)Classificadn & Representn..
2) Multivariate Linear Regr.
2) Logistic Regression Model
3) Computing Parantis Analte.
3) Multiclans Classificadn.
4) Submi Hing Aogr. Aseignts.
4) Review Sluiz
5) Review Quiz
5) solving the Aeb. Overfitting
6) Delave/MATLAB Tutorial
6) Review suiz
7) Review Quit
Arogramming Assignment
WEEK #5
1) Cost fon & Back propagatn
2) Backpropagatn in practice
3) Applicatn of NN
4) Review (QU12+ Ρ.Α.)
WEEK #8
1) Clustering
2) Review (QU12)
3) Motivatn
4) PCA Analysis
5) Applying PCA
6) Review (QU12+ P.Α.)
WEEK #11
WEEK #10
Grad. Desc, with Large Datasets
1) Photo OCR
Advanced Topics
Review (0412)
2) Review (8412)
3) Conclusion.
Programming Assignment.
WEEK #6
1) Evaluating a lesin. Alger.
2) Bias vs. Variance
3) Review (9412+P.Α.)
4) Building a span Classike
5) Hardling showed cada
6) Waing Large Doda seb
WEEK #9
1) Density Estimat
2) Building a Anomaly Dots
3) Multivariate Gous. Diet
4) Review (QU12)
5) fredicting Movie Rating
5) Collaborate Filtering
9) Low Rank Mix Factorgt
8) Review (QU12+ P.A.)
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