clean up markdown and structure

shensquared · shensquared · commit 6fac3bb5ab33 · 2023-06-15T11:57:50.000-04:00
diff --git a/about.markdown b/about.markdown
diff --git a/about.md b/about.md
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+---
+layout: page
+title: About
+permalink: /about/
+nav_order: 1
+---
+
+# Course overview
+
+- Graduate level; offered in the Fall only
+- 12 units (3-0-9)
+- Prerequisites:
+  - Linear algebra (at the level of 18.06)
+  - and Probability (at the level of 6.3700, 6.3800, or 18.600)
+- Brief description: Principles, techniques, and algorithms in machine learning from the point of view of statistical inference; representation, generalization, and model selection; and methods such as linear/additive models, active learning, boosting, support vector machines, non-parametric Bayesian methods, hidden Markov models, Bayesian networks, and convolutional and recurrent neural networks. Recommended prerequisite: 6.3900 or other previous experience in machine learning. Enrollment may be limited.
+
+# Staff
+
+- Instructors
+- TAs
+
+# Logistics
+
+- Lectures: Tuesday and Thursday, 2:30pm in 32-123
+- Recitations: Friday,
+- Office hours:
+  - Instructor office hours: TBD
+  - TA office hours: TBD
+
+# Grading
+
+- Homework
+- Exams
+
+# Recommended Reading
+
+- [B] Pattern Recognition and Machine Learning, Bishop; Springer, 2007.
+- [EH] Computer Age Statistical Inference, Efron and Hastie; Cambridge University Press, 2016.
+- [JWHT] An Introduction to Statistical Learning, James, Witten, Hastie, Tibshirani; Springer, 2013. Easy read, very pragmatic.
+- [SB]/[SSS] Understanding Machine Learning: From Theory to Algorithms, Shalev-Shwartz and Ben-David, 2014.
+- [HTF] The Elements of Statistical Learning, Hastie, Tibshirani, Friedman, 2009.
+- [S] Introduction to Reinforcement Learning, Sutton, 2018.
diff --git a/index.markdown b/index.markdown
diff --git a/index.md b/index.md
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+---
+layout: page
+---
+
+The site is under construction for launch in the fall 2023 semester.
diff --git a/intro.markdown b/intro.markdown
diff --git a/intro.md b/intro.md
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+---
+layout: page
+title: Introduction
+# permalink: /intro/
+nav_order: 2
+---
+
+Machine Learning is ...
+
+Typically, we can break machine learning problems down into three categories, [supervised learning](supervised/), [unsupervised learning](/unsupervised/), and [reinforcement learning](/reinforcement/).
diff --git a/reinforcement.md b/reinforcement.md
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+---
+layout: about
+title: Reinforcement Learning
+has_children: true
+nav_order: 6
+
+---
diff --git a/reinforcement/bandit.md b/reinforcement/bandit.md
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+---
+layout: about
+title: Bandits
+parent: Reinforcement Learning
+nav_order: 2
+---
diff --git a/reinforcement/mdp.md b/reinforcement/mdp.md
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+---
+layout: about
+title: Markov Decision Process
+parent: Reinforcement Learning
+nav_order: 1
+---
diff --git a/reinforcement/reinforcement.md b/reinforcement/reinforcement.md
diff --git a/review.md b/review.md
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+---
+layout: page
+title: Review
+permalink: /review/
+nav_order: 3
+
+---
+
+# Review lecture
+
+## Notations
+
+- Data matrix is of the size $$(n,d)$$ where $n$ is the number of data points, and $$d$$ is the dimension of the features
+- Vectors are denoted with a small-case letter; matrices capital letters
+- The default norm of a vector is the $l_2$ norm
+
+## Linear algebra, calculus, and optimization
+
+- Gradient
+- PSD/PD
+- Convexity, strong convexity
+- Optimal solutions, uniqueness
+
+## Probability theory and Statistics
+
+### Concepts related to a single distribution
+
+- Multi-variate normal distribution
+- Max likelihood and Max log likelihood
+
+### Concepts involving multiple distributions
+
+- Marginal independence
+  - Joint probability is the product
+  - Entropy of the joint distribution is the sum of individual entropies
+- Bayes' rule
+- Conditional independence
+  - Compare with marginal independence
+- Importance sampling
+- Jensen inequality
+- KL divergence
diff --git a/supervised.md b/supervised.md
@@ -1,6 +1,6 @@
 ---
 layout: about
-title: Unsupervised
+title: Supervised Learning
 has_children: true
 nav_order: 4
 
diff --git a/supervised/linearRegression.md b/supervised/linearRegression.md
@@ -1,5 +1,5 @@
 ---
 layout: about
 title: Linear Regression
-parent: Supervised
+parent: Supervised Learning
 ---
diff --git a/supervised/supervised.md b/supervised/supervised.md
diff --git a/unsupervised.md b/unsupervised.md
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+---
+layout: about
+title: Unsupervised Learning
+has_children: true
+nav_order: 5
+
+---
diff --git a/unsupervised/graphical.md b/unsupervised/graphical.md
@@ -3,5 +3,5 @@ layout: about
 title: Graphical
 has_children: true
 nav_order: 4
-parent: Unsupervised
+parent: Unsupervised Learning
 ---

-Original file line number
+Diff line change
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 +---
 +layout: page
 +---
++
 +The site is under construction for launch in the fall 2023 semester.