🪴 Aster's study notes

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39 items under this folder.

Oct 10, 2023
Supervised learning
- #2-ref
Oct 10, 2023
Z-value
- #2-ref
Oct 10, 2023
P-value
- #2-ref
Oct 10, 2023
Maximum likelihood
- #2-ref
Oct 10, 2023
Logistic regression
- #2-ref
Oct 10, 2023
Decision tree and random forest
- #2-ref
Oct 08, 2023
Bootstrapping
- #2-ref
Oct 08, 2023
Confidence intervals
- #2-ref
Oct 08, 2023
Histogram
- #2-ref
Oct 08, 2023
Mathematical model
- #2-ref
Oct 08, 2023
Mean, variance and standard deviation
- #2-ref
Oct 08, 2023
Normal distribution
- #2-ref
Oct 08, 2023
Population and estimated parameters
- #2-ref
Oct 08, 2023
Probability distribution
- #2-ref
Oct 08, 2023
Random sampling
- #2-ref
Oct 08, 2023
Resampling
- #2-ref
Oct 08, 2023
Sampling a distribution
- #2-ref
Oct 08, 2023
t-test
- #2-ref
Oct 07, 2023
Stats
- #moc
Oct 05, 2023
Probability
- #moc
Oct 04, 2023
Bayes classifier
- #2-ref
Oct 04, 2023
Classification
- #2-ref
Oct 04, 2023
Linear discriminant analysis (LDA)
- #2-ref
Oct 03, 2023
Bayes' theorem
- #2-ref
Oct 03, 2023
Prior probability and posterior probability
- #2-ref
Oct 02, 2023
Linear regresssion
- #2-ref
Oct 02, 2023
Bayesian statistics
- #2-ref
Oct 02, 2023
Bias variance trade off
- #2-ref
Oct 02, 2023
Classification error metrics
- #2-ref
Oct 02, 2023
K nearest neighbours (KNN) with python
- #2-ref
Oct 02, 2023
K nearest neighbours (KNN) theory
- #2-ref
Oct 02, 2023
Linear regresssion in python
- #2-ref
Oct 02, 2023
Python
- #moc
Oct 02, 2023
R
- #moc
Oct 02, 2023
Regression error metrics
- #2-ref
Oct 02, 2023
Data science
- #moc
Oct 02, 2023
Machine learning
- #moc
Oct 01, 2023
Logistic regression in python
- #2-ref
Oct 01, 2023
Logistic regression coefficients
- #2-ref

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