Free online courseMachine Learning

Course content

• Video class: Lecture 1 | Machine Learning (Stanford)

  1h08m

• Exercise: What is emphasized as a key advantage of learning algorithms in the class?

• Video class: Lecture 2 | Machine Learning (Stanford)

  1h16m

• Exercise: Which of the following describes what an “alvin” is?

• Video class: Lecture 3 | Machine Learning (Stanford)

  1h13m

• Exercise: What is a key characteristic of locally weighted regression?

• Video class: Lecture 4 | Machine Learning (Stanford)

  1h13m

• Exercise: What is one advantage of Newton's method over gradient descent?

• Video class: Lecture 5 | Machine Learning (Stanford)

  1h15m

• Exercise: What do you learn in a discrimitive learning algorithms?

• Video class: Lecture 6 | Machine Learning (Stanford)

  1h13m

• Exercise: How does Naive Bayes handle text classification differently in its event models?

• Video class: Lecture 7 | Machine Learning (Stanford)

  1h15m

• Exercise: What is a key mathematical constraint in deriving the optimal margin classifier in support vector machines?

• Video class: Lecture 8 | Machine Learning (Stanford)

  1h17m

• Exercise: Which algorithm allows SVMs to handle non-linearly separable data?

• Video class: Lecture 9 | Machine Learning (Stanford)

  1h14m

• Exercise: What is the effect of expanding the hypothesis class on the generalization error?

• Video class: Lecture 10 | Machine Learning (Stanford)

  1h12m

• Exercise: What is the VC dimension in the context of linear classifiers?

• Video class: Lecture 11 | Machine Learning (Stanford)

  1h22m

• Exercise: His advices are good if you want to:

• Video class: Lecture 12 | Machine Learning (Stanford)

  1h14m

• Exercise: What is the primary function of the K-means clustering algorithm discussed in the presentation?

• Video class: Lecture 13 | Machine Learning (Stanford)

  1h14m

• Exercise: What key advantage does the EM algorithm provide when applied to complex models?

• Video class: Lecture 14 | Machine Learning (Stanford)

  1h20m

• Exercise: What is a common application of PCA in data analysis?

• Video class: Lecture 15 | Machine Learning (Stanford)

  1h17m

• Exercise: What is the primary goal of PCA in data analysis?

• Video class: Lecture 16 | Machine Learning (Stanford)

  1h13m

• Exercise: What MDP means?

• Video class: Lecture 17 | Machine Learning (Stanford)

  1h17m

• Exercise: What is fitted value iteration used for?

• Video class: Lecture 18 | Machine Learning (Stanford)

  1h16m

• Exercise: What is the role of the Riccati Equation in finite Horizon LQR problems?

• Video class: Lecture 19 | Machine Learning (Stanford)

  1h15m

• Exercise: Which of the following is the first step if you want to design a controller to a helicopter?

• Video class: Lecture 20 | Machine Learning (Stanford)

  1h16m

• Exercise: What is a key challenge in computing the optimal policy for partially observable MDPs (POMDPs)?