added stubs for the upcoming sections

deep-learning-intro-for-hep/exercise-5.md

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+
+# Exercise 5: L1 and L2 regularization

deep-learning-intro-for-hep/exercise-6.md

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+
+# Exercise 6: Dropout regularization

deep-learning-intro-for-hep/goodness-of-fit.md

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+
+# Goodness of fit metrics

deep-learning-intro-for-hep/hyperparameters.md

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+
+# Parameters and hyperparameters

deep-learning-intro-for-hep/main-project.md

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+
+# The main project

deep-learning-intro-for-hep/partitioning.md

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+
+# Partitioning data into training, validation, and test samples

deep-learning-intro-for-hep/regularization.md

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+
+# Regularization
+
++++
+
+Notes:
+
+- https://doi.org/10.2307/1271436 _Ridge Regression: Biased Estimation for Nonorthogonal Problems_ ARTHUR E. HOERL AND ROBERT W. KENNARD 1970
+- Regression Shrinkage and Selection via the Lasso https://doi.org/10.1111/j.2517-6161.1996.tb02080.x _Regression Shrinkage and Selection Via the Lasso_ Robert Tibshirani 1996
+
+Do the Boston dataset here, and then exercise 1 is with Playground, exercise 2 is dropout with penguins