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Decks in this class (25)
Designing a classifier and Bayes' decision rule
Draw the pipeline of designing a ...,
What is the sensor stage of desig...,
What is the feature generation st...
27
cards
Probability Density Functions
For continuous random variables w...,
What does the probability density...,
How do you calculate a probability 3
7
cards
Processing multivariate data
What is multivariate data 1,
How is a multivariate observation...,
If there are multiple samples for...
15
cards
Parameter Estimation (needs practice (mixups))
Describe the parametric approach ...,
What does p x means 2,
What is the parameter likelihood ...
13
cards
Minimising Risk (formulas need work)
What is feature space 1,
What is the decision boundary 2,
In 2d feature space how many dime...
16
cards
Distance Measures and Multivariate Distributions
The dot product of x and y is equ...,
If x is perpendicular to y what w...,
When it is a column by a row vect...
16
cards
Linear Classifiers
What does p x y represent 1,
Define a joint cumulative distrib...,
What do the parameters of the uni...
14
cards
Linear Separability
What is a linear classifier 1,
Rewrite the decision boundary for...,
What is the discriminant function...
5
cards
Linear Discriminant Boundaries
What is the formula for the decis...,
What is the formula for the decis...,
How do you calculate the discrimi...
8
cards
Non-Parametric Classifiers
How is a non parametric classifie...,
5 factors of non parametric class...,
Advantages of parametric classifi...
19
cards
K Nearest Neighbour Classifier
What is support vector machines 1,
Strengths and weakness of support...,
What is the nearest neighbour rule 3
11
cards
Condensed Nearest Neighbours and Performance Metrics
What is the computational complex...,
Difference between parameters and...,
What is condensed nearest neighbo...
16
cards
Introduction to Feature Selection
What is divergence 1,
Give the formula for divergence d...,
Give the formula for the symmetri...
10
cards
Feature Selection Algorithms
Describe the 2 methods of feature...,
Key characteristics of scalar met...,
Common techniques of scalar metho...
17
cards
Dimensionality Reduction by Linear Transformation
What is the curse of dimensionali...,
Problem with feature selection 2,
Describe the process of dimension...
4
cards
Principal Component Analaysis
What is the basic idea of pca for...,
How can we bring the mean error d...,
Describe the principal axis 3
14
cards
Perceptron Learning Algorithm (pseudocode)
Describe the perceptron learning ...,
What is the purpose of the traina...,
Explain the steps to an artificia...
14
cards
Perceptron Learning Algorithm P2
How do you find the best set of w...,
Define the cost function j w 2,
Is j w always positive or negative 3
9
cards
Perceptron with Logistic Activation Function (formulas)
What is the step activation funct...,
Give the formula for the logistic...,
Advantages of a logistic function...
15
cards
Multilayer Perceptron and Deep Learning (haven't properly done)
Xor is a non linear separable pro...,
What does the 3 represent in neur...,
What is a multilayer perceptron f...
18
cards
Training Multilayer Perceptron (haven't properly done)
Formula for the forward pass when...,
Why is binary cross entropy the m...,
Formula for binary cross entropy ...
12
cards
Introduction to Clustering
What is clustering 1,
Use cases of clustering 2,
5 basic steps to clustering 3
12
cards
Hierarchical clustering and K-Means (restart)
Describe the nesting process in h...,
What are the 2 types of hierarchi...,
What is agglomerative clustering 3
14
cards
Soft Clustering
What is soft clustering and its c...,
What is soft k means 2,
How is the u calculated to determ...
6
cards
FORMULAS
Formula for posterior probability...,
Simple formula to decide which cl...,
Formula for guassian distribution 3
39
cards
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Y2 Data Driven Computing
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