**Concise Introduction to Deep
Neural Networks:** slidedeck

**Introduction to Support Vector
Machines:** slidedeck

**Introduction to Probability:**

Some good references
include:

• H. Stark
and J.W. Woods. Probability, Statistics and Random Processes for Engineers.
Prentice-Hall.

• Sheldon
Ross. A First Course in Probability.
Pearson.

• Santosh S.
Venkatesh.The Theory of
Probability: Explorations and Applications. Cambridge.

•
Y.A. Rozanov. A concise
course in probability. Dover publishers.

My slide-deck for
this course is here: slidedeck

A tricky proof for a problem of
best-of games is here: best-of-games

Notes on single-player craps: craps

**Introduction to Frequency
Domain Analysis of Linear and Time-Invariant Systems:**

At PSU, the course is
EE 350 (or EE 353 for non-EE majors) and the reference is B.P. Lathi’s book,
“Signal Processing & Linear Systems.”

A very useful
resource with lots of solved problems and exams is
http://courses.ee.psu.edu/schiano/EE350

My slide-deck for this
course is here: slidedeck** **

My slide-deck for the
discrete-time material is here: slidedeck** **

**Introduction to Probability
Theory:**

**Introduction to Discrete
Mathematics:**

At PSU, the course is
CMPSC 360 and the reference I’ve used in the past is the book by S. Epp.

My slide-deck for
this course, largely cobbled together from those of others, is here: slidedeck

My slide-deck for an
introduction to graph theory is here: slidedeck

**Introduction to Performance
Evaluation:**

My slide-deck for
this course is here: slidedeck