Code stuff
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✅ Get rid of init stuff
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✅ leading underscores for hidden methods
Text
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✅ output/outcome/response
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✅ Model set-up
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✅ log likelihood
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✅ sklearn
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✅ multi-class
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✅ non-linear
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✅ underline vs. headers for "model set up" and other section labels
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✅ In Generative classifiers, maybe change labels to prior and likelihood (rather than p(y) and p(x|y))
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✅ Link vs.
do this
for dataset names
Notation/convention
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"linear combination"
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✅Add a thing to the conventions note about L(theta; data). Note that data might be represented as upper case or lower case
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✅add a thing about { }_{n = 1}^N
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✅ Make r.v.s upper case
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✅ make matrices bold
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✅ change losses to L
Content changes
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✅ Gradient ascent vs. descent
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✅ add mention of linear (no) activation function in NNs
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✅ Neural nets make
$\bx \in \R^{D_X}$ and$\by \in \R^{D_y}$ . -
✅ Change wine dataset to cancer in c3 binary stuff
Things to review
- Appendix
THINGS TO ADD
- C2 ARIMA
- C2 nonparametric regression (with kernels)
- Unsupervised
- SVMs