Machine learning questions:
- What is a learning algorithm?
- What is the difference between the training, validation and test sets?
- What is supervised learning?
- What is unsupervised learning?
- What is empirical risk minimization?
- What is stochastic gradient descent?
- What is the capacity of a model?
- What is the difference between a parametric and a non-parametric
- What is the difference between a parameter and a hyper-parameter?
- What is generalization?
- What is the difference between under-fitting and over-fitting?
- What is model selection?
- What is regularization?
- What is the bias variance trade-off?
Linear algebra review:
- What is a derivative?
- What is a partial derivative?
- What is a gradient?
- What is the chain rule?
- What is a Hessian matrix?
- What is a matrix? What is a vector?
- How to perform products between matrices and vectors?
- What are the following properties of matrices?
- identity matrix
- diagonal matrix
- transpose matrix
- symmetric matrix
- orthogonal matrix
- positive semidefinite matrix
- What are the following operations on a matrix and their properties?
- trace of a matrix
- norm of a matrix
- inverse of a matrix
- determinant of a matrix
- What is the concept of linear dependance between vectors?
- What is the rank of a matrix?
- What are the range and nullspace of a matrix?
- What are the eigenvalues and eigenvectors of a matrix, and what are
- How does the concept of gradient generalize to vectors and matrices?
- What is a probability space?
- What is a random variable?
- What is a distribution?
- What is are joint, marginal and conditional distributions?
- When are random variables independent?
- What is the probability chain rule?
- What is the Bayes rule?
- What is the difference between a discrete and continuous distribution?
- What is are density and cumulative distribution functions?
- What are the expectation and variance of a random variable?
- What are the Bernoulli, Poisson and Gaussian distributions?
- What is Jensen's Inequality?
- How to estimate the expectation or variance of a random variable from samples?
- What is a confidence interval?
- What is a simple Monte Carlo estimate?
- What is direct sampling?
- What is rejection sampling?
- What is importance sampling?
- What is Markov Chain Monte Carlo?
- What is Metropolis Hastings?
- What is Gibbs sampling?
- What is the Python interpreter?
- How to manipulate numbers and strings in Python?
- What is the syntax of control flow statements (if, for, etc.) in
- How to use the common data structures (Lists, Tuples, Sets and
Dictionaries) in Python?
- How to define functions and classes?
- What are modules and packages?
- How to read and write in files?
- What is and how to use Pickle (and cPickle)?
- How to do linear algebra with Numpy?
- How to debug in Python?
- How to download and load a dataset?
- What are MLProblems and how to manipulate them?
- What are Learners?
- How to perform a machine learning experiment with MLPython?