Miscellaneous Topics

Avishek Sen Gupta on 6 April 2021

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Miscellaneous Topics

• Newton-Raphson Method
• Gradient Descent and Stochastic Gradient Descent
• Dynamic Programming
• Missing Data and Data Imputation
• L1 and L2 Regularisation
• p-values and hypothesis testing
• Bagging and Boosting
• Expectation Maximisation
• Naive Bayes
• Cross Validation
• k-means clustering
• Basic Explanations of Expectation and Conditional Probability
• Latest ML Papers
• Relationship between MLE and MAP
• Multivariate Gaussian and the Covariance Matrix
• Quadratic Approximation
• Logistic Regression MLE Cost Function
• Bayesian interpretation of Linear Regression
• Basic Probability, Expectation, etc.
• Gaussian Processes and Intuition
• Information Geometry

• Singular Value Decomposition

• ML Practice
  • Newton-Raphson Method
  • Gradient Descent and Stochastic Gradient Descent
  • Dynamic Programming
  • Sequential Minimal Optimisation
  • Schur Complement
  • Cholesky Factorisation

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