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AWS (Data Scientist (Math for Machine Learning (Probability (Probability…

- - - - Vectors and Matrices
      - Geometry of Column Vectors
      - Measures of Magnitude
      - Vectors in Code
    - - Motivation
      - Dot Products
      - Matrix Multiplication
      - The Hadamard Product
      - Product Properties
        
        Distributivity
        
        Associativity
        
        Commutativity
        
        Identity Matrix
        
        Hadamard product
      - Geometry Matrix Operation
        
        Stretching
        
        Skewing
        
        Rotation
      - Determinant Computation
      - Invertibility
    - - Axioms of probability
      - Visualizing Probability
        
        Probability represented with Venn diagrams
      - Conditional probability
      - Bayes’ rule
      - Independent
        
        Events and Notation
      - Discrete Random Variables
      - Chebyshev’s inequality
      - Entropy
      - The Gaussian
      - A Word on Building Models
      - Intuition
        
        Inherently Random
        
        Too complex
      - Probability Terminology
        
        Outcome
        
        Sample Space
        
        Event
        
        Probability
      - Continuous random variables
    - - Univariate Derivative Calculus
      - Maximum Likelihood Estimation: A Motivation for Calculus
      - Derivatives
      - Second Derivatives
      - Gradient Descent
      - Newton’s Method
      - Summary
    - - Intuition
      - Partial Derivatives
      - Gradient
      - Matrix Calculus
      - Second Derivatives
      - Newton’s Method
      - Convexity