probability for ml

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Decks in this class (21)

Chapter 4 Joint, Marginal, and Conditional Probability
What is the definition of join ma...,
How is joint probability shown p 39,
How is joint probability calculat...
13  cards
Chapter 7 Probability Distributions
What is a random variable p 64,
Upper case letters like x denote ...,
What are the values of a random v...
18  cards
Chapter 8 Discrete Probability Distributions
What is the inverse of pdf called...,
What is a bernoulli trial give an...,
What s a bernoulli process p 71
12  cards
Chapter 9 Continuous Probability Distributions
Define pdf cdf ppf p 79,
A normal distribution with a mean...,
How can we create a simulated nor...
16  cards
Chapter 10 Probability Density Estimation
We rarely do know the distributio...,
Reviewing a histogram of a data s...,
What is parametric density estima...
18  cards
Chapter 11 Maximum Likelihood Estimation
There are many techniques for sol...,
How does maximum likelihood estim...,
For what purpose is maximum likel...
14  cards
Chapter 12-13 Linear/Logistic Regression With Maximum Likelihood Estimation
The parameters of a linear regres...,
A linear regression model can be ...,
Calculating the negative of the l...
3  cards
Chapter 14 Expectation Maximization (EM Algorithm)
Why is expectation maximization u...,
What is a latent variable give an...,
Expectation maximization is an ef...
15  cards
Chapter 15 Probabilistic Model Selection with AIC, BIC, and MDL
It is common to choose a model th...,
What s one benefit and one limita...,
The simplest reliable method of m...
17  cards
Chapter 16 Introduction to Bayes Theorem
P ab p ba true false p 150,
One conditional probability can b...,
What is the definition of bayes t...
8  cards
Chapter 17 Bayes Theorem and Machine Learning
How can we frame a hypothesis and...,
Under bayes framework each piece ...,
What do we want to maximize when ...
16  cards
Chapter 19 How to Implement Bayesian Optimization
What s bayesian optimization p 179,
What s an objective function exte...,
What s global function optimizati...
30  cards
Chapter 20 Bayesian Belief Networks
What is conditional dependence ex...,
What is the challeng of designing...,
What is a common approach to addr...
21  cards
Chapter 21 Information Theory
Information theory is a subfield ...,
Calculating information and entro...,
Information theory is concerned w...
14  cards
Chapter 22 Divergence Between Probability Distributions
There are many situations where w...,
What s a the divergence between t...,
What does this mean divergence is...
11  cards
Chapter 23 Cross-Entropy for Machine Learning
What s cross entropy how is it us...,
Cross entropy is closely related ...,
What s the intuition behind cross...
12  cards
Chapter 24 Information Gain and Mutual Information
Information gain is calculated by...,
How can entropy be used as a calc...,
A smaller entropy suggests ____ l...
14  cards
Chapter 25 How to Develop and Evaluate Naive Classifier Strategies
Given a classification model how ...,
How do naive classifiers make pre...,
Given not all naive classifiers a...
4  cards
Chapter 26 Probability Scoring Metrics
Log loss also called ____ ____ or...,
The log loss can be implemented i...,
Why is log loss not suitable for ...
14  cards
Chapter 27 When to Use ROC Curves and Precision-Recall Curves
What s the reason for predicting ...,
What s another name for precision...,
What s a no skill model represent...
7  cards
Chapter 28 How to Calibrate Predicted Probabilities
Predicted probabilities that matc...,
Although a model may be able to p...,
There are two concerns in calibra...
10  cards

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probability for ml

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