CS 4540 (F18) Entry Survey
Welcome to CS 4540 at Georgia Tech! Please fill out this short (~5-10min) survey to help us get to know the class better! Your response is completely anonymous.
What is your major?
Computational Sci & Engr
If your major is Computer Science, which "threads" are you working towards?
Modeling & Simulation
Systems & Architecture
Have you used any of the following before?
Check all that apply.
Numpy / Matplotlib / SciPy
No, I haven't.
PREREQUISITES & OTHER COURSES
Prerequisites: Calculus + Analysis
Have you taken a calculus class before? Check all that apply.
Calc I + II (single-variable differentiation and integration)
Calculus III (multivariate differentiation and integration)
Advanced Calculus (proof-based; lots of epsilons and deltas)
I have never taken a calculus class.
Prerequisites: Linear Algebra
Have you taken a linear algebra class before? Check all that apply.
Intro Linear Algebra
Advanced Linear Algebra (e.g. minimal polynomials, invariant subspaces, Jordan canonical forms...)
Numerical Linear Algebra (e.g. QR factorization, Gauss-Seidel iteration, conjugate gradient...)
I have never taken a linear algebra class.
Have you taken a probability class before? Check all that apply.
Intro Probability (no calculus)
Measure-theoretic Probability (Lebesgue integrals, sigma-algebras, MCT, etc.)
I have never taken a probability class.
Have you taken or are you currently taking any of the following courses?
Machine Learning (e.g. CS 3600, CS 4641, CS 4646)
Artificial Intelligence (e.g. CS 3600, CS 4731, CS 4635)
Linear Programming (e.g. MATH 4580)
Numerical Analysis (e.g. MATH 4640)
Information Theory (e.g. MATH 4280)
Which of the following topics have you studied before? Check all that apply. Topics marked with (*) will not be needed for this course and are only included here to gauge your prior knowledge.
Concepts: Calculus & Analysis
Gradient of a function f : R^n --> R
Differential of a function f : R^n --> R^m
Rigorous definition of a limit (for all epsilon > 0, exists delta > 0 such that...)
Maximizing a multivariable function; Lagrange multipliers for equality constraints
Convex function optimization; Lagrange duality; convex conjugates
(*) Inverse Function Theorem / Implicit Function Theorem
(**) Measure theory (Lebesgue integrals, monotone convergence, Radon-Nikodym...)
I have never studied calculus.
Concepts: Linear Algebra
Matrices, vectors, and matrix multiplication
Basis vectors, change of basis; orthogonal vectors, Gram-Schmidt
Eigenvalues and eigenvectors
Abstract vector spaces, linear transformations
Positive-definite matrices and their eigenvalues
Solving linear systems via least-squares; Moore-Penrose pseudoinverse
Matrix Decompositions (SVD, QR, etc.)
(*) Invariant subspaces
(*) Minimal polynomials, Cayley-Hamilton
I have never studied linear algebra.
Concepts: Probability & Statistics
Discrete distributions, random variables, expectation, variance
Continuous distributions, random variables, expectation, variance
Independence; expectation and variance of independent random variables
Normal distribution, central limit theorem
Markov and Chebychev inequalities
Hoeffding and Chernoff bounds
Bayesian statistics, prior and posterior distributions, conjugate priors, exponential families
I have never studied probability.
What do you hope to learn from this class?
Is there anything else you'd like to tell us? (hopes, dreams, concerns...)
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