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Course content
- Set Theory
- Combinatorics
- Probability – Basics/General
- Theoretical Probability
- Empirical Probability
- Probability – Addition Rule
- Probability – Multiplication Rule
- Conditional Probability
- Theorem of Total Probability
- Probability – Decision Tree
- Bayes’ Theorem
- Sensitivity and Specificity in Probability: Diagnostic Test Performance
- Binomial, Poisson & Normal Distributions, Z-Score, Skewness, Kurtosis
- Geometric Distribution
- Hypergeometric Distribution
- Markov Chain
- Linear Algebra – Matrices
- Linear Algebra – Determinant
- Linear Algebra – EigenVaIue and EigenVector
- Euclidean Distance and Manhattan Distance
- NumPy – Recommendation! Recommendation!! Recommendation!!!
- Statistics
- Statistics – Mean
- Statistics – Weighted Mean
- Statistics – Properties of Mean
- Statistics – Mean Frequency Distribution
- Statistics – Median
- Statistics – Median Frequency Distribution
- Statistics – Mode
- Statistics – Mode Frequency Distribution
- Statistics – Measurement of Spread
- Statistics – Range
- Statistics – Mean Deviation
- Statistics – Variance & Standard Deviation
- Statistics – Variable I Dependent- Independent – Moderating – Ordinal…
- Statistics – Correlation
- Statistics – Regression & Collinearity
- Statistics – Pearson and Spearman Correlation Methods
- Statistics – Regression Error Metrics
- Indices & Logarithms
- Entropy in Machine Learning
- Information Gain
- Surprise in Machine Learning
- Loss Function, Cost Function and Error Function
- Mean Squared Error Loss Function
- Mean Absolute Error Loss Function
- Huber Loss Function
- Cross Entropy Loss Function
- Categorical Cross-Entropy Loss Function
- Hinge Loss Function
- Calculus – Introduction to Differentiation
- Calculus – Derivatives By First Principle
- Calculus – Second Derivatives
- Calculus – Special Derivatives
- Calculus – Differentiation Using Chain Rule
- Calculus – Differentiation Using Product Rule
- Calculus – Differentiation Using Chain and Product Rules I Examples
- Calculus – Differentiation Using Quotient Rule
- Calculus – Differentiation Using Quotient and Chain Rules I Examples
- Integration – Introduction
- Integration – Indefinite Integrals
- Integration – Indefinite Integrals II
- Integration – Definite Integrals I
- Integration – Definite Integrals II
- Area Under Curve – Using Integration
- ARCHIVED – Set Theory
- ARCHIVED – Combinatorics
- ARCHIVED – Probability – Basics/GeneraI
- ARCHIVED – Theoretical Probability
- ARCHIVED – Empirical (Experimental) Probability
- ARCHIVED – Probability Addition Rules
- ARCHIVED – Probability Multiplication Rule
- ARCHIVED – Probability – Tons of Exercises & Solutions
- ARCHIVED – Conditional Probability
- ARCHIVED – Theorem of Total Probability
- ARCHIVED – Bayes’ Theorem
- ARCHIVED – Bayes’ Theorem, Total Probability and Depend Events – Decision Tree
- ARCHIVED – Linear Algebra – Matrices
- BONUS SECTION
