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Machine Learning

This class was created by Brainscape user Alexander Bazba. Visit their profile to learn more about the creator.

By: Alexander Bazba
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Decks in this class (11)

Lecture 1 - Introduction
What is machine learning about,
What are tasks,
What are predictive tasks
41  cards
Lecture 2 - Binary Classification
Binary Classification and Related tasks
32  cards
Lecture 3 - Multi-class classification and regression
Give an example of multi class cl...,
What are the two approaches to tu...,
What is one versus rest
26  cards
Lecture 4 - Tree models
What are the three models based o...,
What are the three parts of a dec...,
What is the max depth and max num...
26  cards
Lecture 5 - Distance based models
What are distance based algorithms,
____ that are closest to the inst...,
What is hamming distance
25  cards
Lecture 6 - Linear Models
What kind of model are linear models,
What are linear functions,
What do geometric concepts such a...
29  cards
Lecture 7 - Features
What are the 4 stages of data pre...,
What are features,
What are the three main categorie...
36  cards
Lecture 8 - Probabilistic models
What are the two interpretations ...,
What is frequentist interpretatio...,
What is bayesian interpretation
15  cards
Week 9 - Model ensembles
What are the three types of model...,
What are model ensembles,
If p 1 2 this implies
41  cards
Week 11 - Explainability
Why do de need reasons for interp...,
What is explaining predictions in...,
What are interpretable models
18  cards
Week 12 - AutoML
What is automl,
What are the benefits of grid search,
What are the advantages and disdv...
7  cards

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Machine Learning

  • Class purpose General learning

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