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COMP61011- Foundations of Machine Learning

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

By: Anna L
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Decks in this class (11)

Chapter 1- Introduction
What is machine learning,
What does it mean to learn,
What is supervised learning
11  cards
Chapter 2- Probabilistic Models
What is a random variable,
What is a sample space or alphabet,
What is an event
39  cards
Chapter 3- Linear Models
What is a decision stump,
What is the decision boundary in ...,
What is the learning algorithm fo...
56  cards
Chapter 4- Experimental Methods 1
What is model selection,
What is cross validation error,
What makes a model more stable
15  cards
Chapter 5- Experimental Methods 2- ROC Analysis
Who was one of the earliest adopt...,
Fp rate,
Tp rate
23  cards
Chapter 6- Feature Selection
What is the aim of feature selection,
Why do different types of models ...,
For d features how many possible ...
34  cards
Chapter 7- Distance Based Methods
Give the k nearest neighbour algo...,
What is hamming distance,
How is hamming distance calculated
10  cards
Chapter 8- Neural Networks
What type of neural networks demo...,
What is alex net,
What is a spiking neural network
46  cards
Chapter 9- Decision Trees
Is the process of automatically c...,
Give the id3 algorithm,
What do we risk as we split on fe...
27  cards
Chapter 10- Ensemble Models
What is the principle of committe...,
What three methods can be used to...,
What is the wisdom of crowds
21  cards
Equations
Conditional probability p ab,
Bayes p ab,
Independent events p a b
75  cards

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COMP61011- Foundations of Machine Learning

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