Foundations

Mathematical Foundations

Linear algebra, calculus, probability, statistics and optimisation — the maths behind ML

2,097
lessons
Skills in this topic
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Maths for ML
beginner
Multiply matrices and compute dot products
Probability & Statistics
beginner
Calculate conditional probability and Bayes' theorem
Optimisation
intermediate
Implement gradient descent from scratch
Information Theory
intermediate
Calculate Shannon entropy and cross-entropy loss
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Vector Calculus for Engineers
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Vector Calculus for Engineers
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RStudio for Six Sigma - Hypothesis Testing
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RStudio for Six Sigma - Hypothesis Testing
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Probabilistic Graphical Models 1: Representation
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Probabilistic Graphical Models 1: Representation
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Bayesian Statistics: Mixture Models
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Bayesian Statistics: Mixture Models
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Matrix Calculus for Data Science & Machine Learning
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Matrix Calculus for Data Science & Machine Learning
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Portfolio Risk and Return Analysis
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Portfolio Risk and Return Analysis
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