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layout: post title: "Statistic Machine Learning Notes 1 Introduction" date: 2021-2-22 07:00:00 +0800

categories: [Notes, Statistic Mchine Learning]

Machine Learning includes Supervised Learning, Unsupervised Learning, Reinforcement Learning.

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Supervised Learning:

Given a dataset that contains n samples (x1, y1) (x2, y2)...
Find relation between features and output
and then do prediction

Regression VS Classification

Regression: \ if y is a continuous variable (eg. price predicion)

Classification: \ label is a discrete variable

Unsupervised Learning:

Dataset has no labels

Clustering:

Gaussian mixture model, 
k-means, 
PCA

Use for CV:

Object detection
Objection localization
Image Classification

Use for NLP:

Machine translation

Reinforcement Learning:

Collect data interactively
Try strategy and collect feedbacks
Improve the strategy based on the feedbacks

E.g.:

AI play video games
Alpha Go
MuZero (Dec 2020), Deepmind, more general, play all games. 

Word "Embeddings": \

- Represent words by vectors \\
- Represent relation by direction 

Senticap: \

- Describing Images with Sentiments 

SemStyle: \

- Learning to Caption from Romantic Novels