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5강, Multimodal representation

1강, Self supervised learning

4강, Discrete representation

3강, Contrastive learning

2강. Mutual information

Openai o1, 내 논문에 넣을 수식 만들어줘

OT : After the Proof of Non-convexity in Deep Learning

15강, Data distribution

14강, Manifold hypothesis

13강, Gradient descent

12강, Activation functions

11강, Kernel method

10강, Hypothesis test

9강, Central limit theorem

6강, Concept of probability

8강, Maximum likelihood estimation

5강, Classification

7강, Conditional & Independence

4강, Matrix & Regularization

3강, Linear Transformation

2강, Model with n features

0강, 왜 다들 대학원무새가 된걸까요

1강, Linear models & Correlation

Where will AIs head?

[집현전] Adversarial attack in NLP