urgent-learner / mlentary

quasi-open-source introductory book about machine learning, emphasis on geometry and modern concepts
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Issue-02: Unit 6 - Adding Prerequisites Content #6

Open shumaari opened 1 year ago

shumaari commented 1 year ago

please suggest topics for prerequisites, please provide feedback for this issue

issue created on 20230529

status checks

[ ] task created [x] task completed :writing_hand: currently writing :ok: okayed by sam

overall topics

outline for math topics

  1. Types, Functions and Dependencies, Notation
  2. Linear Algebra: High Dimensions, Hyperplanes, Linear Maps, Trace and Det; Quadratic Forms, Dot Products, SVD
  3. Probability: Expectations, Independence, Bayes, Concentration; Coinflips, Gaussians
  4. Optimization: Visualizing Derivative Rules, Sums of Terms (Constraints); Vectors vs Covectors, Overshooting, Convexity; Gradient Descent
  5. Examples: Least Squares; Gaussian Fitting M-Step

detailed list for math topics

  1. Types, Functions and Dependencies, Notation
  2. Linear Algebra: High Dimensions, Hyperplanes, Linear Maps, Trace and Det; Quadratic Forms, Dot Products, SVD
  3. Probability: Expectations, Independence, Bayes, Concentration; Coinflips, Gaussians; MLE?
    • [ ] :writing_hand: Computing Averages (Expectations)
    • [ ] :writing_hand: Gaussian Random Variable
  4. Optimization: Visualizing Derivative Rules, Sums of Terms (Constraints); Vectors vs Covectors, Overshooting, Convexity; Gradient Descent
  5. Examples: Least Squares; Gaussian Fitting M-Step