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MATHEMATICS_4_AI
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MATHEMATICS_4_AI
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Linear Algebra ==
- Vectors
definition, scalars, addition, scalar multiplication, inner product(dot product), vector projection, cosine similarity, orthogonal vectors, normal and orthonormal vectors, vector norm, vector space, linear combination, linear span, linear independence, basis vectors
- Matrices
definition, addition, transpose, scalar multiplication, matrix multiplication, matrix multiplication properties, hadamard product, functions, linear transformation, determinant, identity matrix, invertible matrix and inverse, rank, trace, popular type of matrices- symmetric, diagonal, orthogonal, orthonormal, positive definite matrix
- Eigenvalues & eigenvectors
concept, intuition, significance, how to find
- Principle component analysis
concept, properties, applications
- Singular value decomposition
concept, properties, applications
Calculus ==
- Functions
- Scalar derivative
definition, intuition, common rules of differentiation, chain rule, partial derivatives
- Gradient
concept, intuition, properties, directional derivative
- Vector and matrix calculus
how to find derivative of {scalar-valued, vector-valued} function wrt a {scalar, vector} -> four combinations- Jacobian
- Gradient algorithms
local/global maxima and minima, saddle point, convex functions, gradient descent algorithms- batch, mini-batch, stochastic, their performance comparison
Probability ==
- Basic rules and axioms
events, sample space, frequentist approach, dependent and independent events, conditional probability
- Random variables- continuous and discrete, expectation, variance, distributions- joint and conditional
- Bayes’ Theorem, MAP, MLE
- Popular distributions- binomial, bernoulli, poisson, exponential, gaussian
- Conjugate priors
Miscellaneous ==
- Information theory- entropy, cross-entropy, KL divergence, mutual information
- Markov Chain- definition, transition matrix, stationarity
== article creds: https://towardsdatascience.com/mathematics-for-ai-all-the-essential-math-topics-you-need-ed1d9c910baf
dc markov