Notes in ML4T

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New Card 10/06/2023 expense ratio noun:
New Card 10/06/2023 Adaptive (Ada) Boost distinction:
New Card 10/06/2023 ETF ticker character count:
New Card 10/06/2023 Mutual fund ticker character counts:
New Card 10/06/2023 AUM abbreviates:
New Card 10/06/2023 AUM noun:
New Card 10/07/2023 ML4TBollinger bands noun:
New Card 10/07/2023 ML4Tleading indicator noun:
New Card 10/07/2023 ML4Tlagging indicator noun:
New Card 10/07/2023 ML4TBollinger bands' indicator type:
New Card 10/07/2023 ML4TDecreasing price hits lower Bollinger band; what do:
New Card 10/07/2023 ML4TIncreasing price hits lower Bollinger band; what do:
New Card 10/07/2023 ML4TEMH abbreviates:
New Card 10/07/2023 ML4Ttechnical data noun:
New Card 10/07/2023 ML4TWeak EMH noun:
New Card 10/07/2023 ML4TSemi-Strong EHM noun:
New Card 10/07/2023 ML4TStrong EHM noun:
New Card 10/07/2023 ML4TSupervised, unsupervised learning distinction:
New Card 10/07/2023 ML4Tlinear regression training time:
New Card 10/07/2023 ML4Tlinear regression query time:
New Card 10/07/2023 ML4Tlinear regression accuracy:
New Card 10/07/2023 ML4Tdecision tree training time:
New Card 10/07/2023 ML4Tdecision tree query time:
New Card 10/07/2023 ML4Tdecision tree accuracy:
New Card 10/07/2023 ML4TkNN training time:
New Card 10/07/2023 ML4TkNN query time:
New Card 10/07/2023 ML4TkNN accuracy:
New Card 10/07/2023 ML4Tbagg abbreviates:
New Card 10/07/2023 ML4Tboostrapping noun:
New Card 10/07/2023 ML4Tbagg decision tree noun:
New Card 10/07/2023 ML4Toverfitting noun:
New Card 10/07/2023 ML4Tparameter vs instance-based model s' distinction:
New Card 10/07/2023 ML4Tto sell "short" a stock etymology:
New Card 10/07/2023 ML4Tto short a stock:
New Card 10/13/2023 ML4Tin-sample backtesting noun:
New Card 10/13/2023 ML4TRSI abbreviates:
New Card 10/13/2023 ML4TPPO indicator abbreviates:
New Card 10/13/2023 ML4TMACD indicator abbreviates:
New Card 10/13/2023 ML4Tto normalize a chart:
New Card 10/27/2023 ML4TIR abbreviates:
New Card 10/27/2023 ML4Tportfolio return definition:\[r_p(t) = {{c1::\beta_p \, r_m(t) + \alpha_p(t)}}\]
New Card 10/27/2023 ML4T\[{\color{lightgray}r_p(t) = {\color{darkorange}\beta_p} \, r_m(t) + \alpha_p(t)}\]\(\beta\) represents:
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