tentative-syllabus.tex

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Each week has classes on Tuesday and Thursday. On Tuesdays, give lectures on mathematical theory; on Thursdays, at least in the half of the semester, have lab-days to work on data sets through computer coding and packages. 


\begin{enumerate}

\item[Week 1:] 
Python, scikit-learn

\item[Week 2:]
(LA) Linear Regression
% Not covered in notes, still needed (?)
%  review or appendix of graham-schmidt and diagonalization of symmetric matrices - needed for next week
%  can include it there.
%  residuals and correlation coefficient
%  standardized variables -- centered is covered but not standardized
%  there's no probability in this section so you can't talk about std error of the coefficients (yet)

\item[Week 3:]
(LA) P.C.A./S.V.D.

\item[Week 4:] 
(LA) Support Vector Machine

\item[Week 5:]
(MC) Gradient Descent

\item[Week 6:] 
(P) Preliminaries on Probability, Bayes' Theorem 

\item[Week 7:]
(P\&MC\&LA) Logistic Regression

\item[Week 8:]
(P) Bayesian Regression 

\item[Week 9:]
(P) Naive Bayes Classifier

\item[Week 10:] 
ROC curve

\item[Week 11:] 
Graph Algorithms

\item[Week 12:] 
Multivaiate Gaussian distributions

\item[Week 13:] 
Sampling

\item[Week 14:] 
Basic Neural Networks

   
\end{enumerate}


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