CMPS 460 | Machine Learning | S22 | Session 8.a | Probabilistic Modeling (Probability Review)
Lecture (a) of Session 8 of
CMPS 460 | Machine Learning | S22 | Session 1.a | Welcome to ML
Lecture (a) of Session 1 of
CMPS 460 | Machine Learning | S22 | Session 1.b | Course outline, Learning & Types of ML
Lecture (b) of Session 1 of
CMPS 460 | Machine Learning | S22 | Session 8.b | Probabilistic Modeling (Naive Bayes I)
Lecture (b) of Session 8 of
CMPS 460 | Machine Learning | S22 | Session 9.g | Neural Networks (Training III)
Lecture (g) of Session 9 of
CMPS 460 | Machine Learning | S22 | Session 9.b | Neural Networks (Representational Power)
Lecture (b) of Session 9 of
CMPS 460 | Machine Learning | S22 | Session 5.c | Practical Issues (Evaluation I)
Lecture (c) of Session 5 of
CMPS 460 | Machine Learning | S22 | Session 3.c | K-means Clustering (I)
Lecture (c) of Session 3 of
CMPS 460 | Machine Learning | S22 | Session 9.a | Neural Networks (Architecture)
Lecture (a) of Session 9 of
CMPS 460 | Machine Learning | S22 | Session 8.c | Probabilistic Modeling (Naive Bayes II)
Lecture (c) of Session 8 of
CMPS 460 | Machine Learning | S22 | Session 8.e | Probabilistic Modeling (Logistic Regression)
Lecture (e) of Session 8 of
CMPS 460 | Machine Learning | S22 | Session 4.c | Perceptron (III)
Lecture (c) of Session 4 of
CMPS 460 | Machine Learning | S22 | Session 2.b | Limits of Learning (II)
Lecture (b) of Session 2 of