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1
Intro
2
What is Personalized Machine Learning?
3
"Traditional" Supervised Machine Learning
4
Personalized Machine Learning: Recommendation
5
Technical setup
6
The Netflix prize
7
More Complex Recommender Systems
8
Model-based vs. contextual personalization
9
Personalized Language Generation & Explanation
10
Generative models of text
11
Generating reviews (example)
12
Personalized explanations (examples)
13
Assistive writing and expansion
14
Persona-grounded dialog
15
Personalized models of visual data
16
Starting point visual models for recommendation
17
Complementary item recommendation
18
Fit prediction
19
Modeling personalized fitness dynamics
20
Conversational recommendation
21
Personalized Design
22
Fairness
Description:
Explore personalized machine learning systems in this 50-minute talk by Julian McAuley, PhD. Discover the principles behind recommender systems, personalized natural language processing, and computer vision applications. Learn about traditional supervised learning, complex recommender systems, personalized language generation, and visual data modeling. Examine the technical setup, model-based vs. contextual personalization, and generative text models. Investigate practical applications like assistive writing, persona-grounded dialog, and complementary item recommendations. Delve into fairness considerations and the consequences of deploying personalized predictive systems in various domains.

Personalized Machine Learning

Open Data Science
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