foundations
42
MLE and classification
Statistics and Machine Learning
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data
1
height data
2
weight data
hypothesis testing
3
one-sample t-test
4
independent samples t-test
confidence interval
5
basic concepts
6
analytical confidence interval
7
empirical confidence interval
permutation
8
the problem with t-test
9
permutation test
10
numpy vs pandas
11
exact vs. Monte Carlo permutation tests
regression
12
the geometry of regression
13
least squares
14
equivalence
15
partitioning of the sum of squares
16
linear mixed effect model
17
logistic regression
18
logistic 2d
correlation
19
correlation
20
correlation and linear regression
21
cosine
22
significance (p-value)
bayes
23
Bayes’ theorem from the ground up
24
parametric generative classification
25
odds and log likelihood
26
logistic connection
27
the boy-girl paradox
28
monty hall
svd and pca
29
SVD for image compression
30
SVD for regression
decision trees
31
CART: classification
32
CART: regression
33
random forest
information theory
34
entropy
35
cross-entropy and KL divergence
foundations
36
probability and likelihood
37
maximum likelihood estimation
38
MLE and summary statistics
39
MLE and linear regression
40
MLE and information theory
41
MLE and regularization
42
MLE and classification
43
MLE and bayesian inference
miscellaneous
44
trend test
foundations
42
MLE and classification
42
MLE and classification
Code
41
MLE and regularization
43
MLE and bayesian inference