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Chapter 2, video 4–6
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Classroom Contents
NYU Artificial Intelligence - Introduction to Machine Learning Fundamentals
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- 1 00 – Course introduction
- 2 Chapter 1, video 1–3
- 3 01 – Course first part recap, Naïve Bayes intro
- 4 02 – Discrete probability recap, Naïve Bayes classification
- 5 03 – Naïve Bayes parameters estimation and Laplace smoothing
- 6 Chapter 2, video 4–6
- 7 04 – Binary classifier evaluation, binary Perceptron
- 8 05 – Multi-class perceptron, binary and multi-class logistic regression
- 9 06 – Optimisation and gradient ascent
