The mathematical foundations of AI, narrated. Linear algebra, calculus, statistics, and classical machine learning, one bite-size lesson at a time. A focused track from Clawdemy.https://clawdemy.org/enCopyright © 2026 RBJ Global LLC. All rights reserved.ClawdemyThe mathematical foundations of AI, narrated. Linear algebra, calculus, statistics, and classical machine learning, one bite-size lesson at a time. A focused track from Clawdemy.Clawdemyhello@clawdemy.orgfalseepisodicce6baeef-1591-51d6-b567-f449c644ed36yesarrpodcasthttps://clawdemy.org/lessons/classical-machine-learning/bias-variance-tradeoff/lesson/https://clawdemy.org/lessons/classical-machine-learning/bias-variance-tradeoff/lesson/Overview of the bias-variance lesson: what you will learn, where it fits, the prerequisite to have first, and the time and difficulty before you start.Mon, 25 May 2026 00:00:00 GMTClawdemy12:00falseOverview of the bias-variance lesson: what you will learn, where it fits, the prerequisite to have first, and the time and difficulty before you start.https://clawdemy.org/lessons/classical-machine-learning/classification-metrics/lesson/https://clawdemy.org/lessons/classical-machine-learning/classification-metrics/lesson/Overview of the classification metrics lesson: what you'll learn about the confusion matrix, precision, recall, ROC and AUC, plus prerequisites and read time.Mon, 25 May 2026 00:00:00 GMTClawdemy13:00falseOverview of the classification metrics lesson: what you'll learn about the confusion matrix, precision, recall, ROC and AUC, plus prerequisites and read time.https://clawdemy.org/lessons/classical-machine-learning/cross-validation/lesson/https://clawdemy.org/lessons/classical-machine-learning/cross-validation/lesson/Overview of the cross-validation lesson: learning outcomes, prerequisites, and time for train/validation/test splits, k-fold CV, and data-leakage traps.Mon, 25 May 2026 00:00:00 GMTClawdemy12:00falseOverview of the cross-validation lesson: learning outcomes, prerequisites, and time for train/validation/test splits, k-fold CV, and data-leakage traps.https://clawdemy.org/lessons/classical-machine-learning/pca/lesson/https://clawdemy.org/lessons/classical-machine-learning/pca/lesson/A map of the PCA lesson: what you'll learn about principal components, scree plots and loadings, plus prerequisites and where it fits in unsupervised learning.Mon, 25 May 2026 00:00:00 GMTClawdemy12:00falseA map of the PCA lesson: what you'll learn about principal components, scree plots and loadings, plus prerequisites and where it fits in unsupervised learning.https://clawdemy.org/lessons/classical-machine-learning/t-sne/lesson/https://clawdemy.org/lessons/classical-machine-learning/t-sne/lesson/What this t-SNE lesson covers: reading 2D cluster plots, what the method preserves and distorts, the perplexity dial, plus prerequisites and time to budget.Mon, 25 May 2026 00:00:00 GMTClawdemy12:00falseWhat this t-SNE lesson covers: reading 2D cluster plots, what the method preserves and distorts, the perplexity dial, plus prerequisites and time to budget.https://clawdemy.org/lessons/visual-math-calculus/higher-order-derivatives/lesson/https://clawdemy.org/lessons/visual-math-calculus/higher-order-derivatives/lesson/Overview of higher derivatives: notation, the second derivative as acceleration and curvature, the second-derivative test, and ML curvature uses.Mon, 25 May 2026 00:00:00 GMTClawdemy10:00falseOverview of higher derivatives: notation, the second derivative as acceleration and curvature, the second-derivative test, and ML curvature uses.https://clawdemy.org/lessons/visual-math-calculus/taylor-series/lesson/https://clawdemy.org/lessons/visual-math-calculus/taylor-series/lesson/A roadmap to the Taylor series: why factorials matter, the e^x, sine, and cosine series, and how gradient descent and Newton's method are Taylor at work.Mon, 25 May 2026 00:00:00 GMTClawdemy12:00falseA roadmap to the Taylor series: why factorials matter, the e^x, sine, and cosine series, and how gradient descent and Newton's method are Taylor at work.https://clawdemy.org/lessons/classical-machine-learning/boosting/lesson/https://clawdemy.org/lessons/classical-machine-learning/boosting/lesson/A quick orientation to boosting: what you'll learn, how it builds on random forests and gradient descent, prerequisites, and time and difficulty.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseA quick orientation to boosting: what you'll learn, how it builds on random forests and gradient descent, prerequisites, and time and difficulty.https://clawdemy.org/lessons/classical-machine-learning/decision-trees/lesson/https://clawdemy.org/lessons/classical-machine-learning/decision-trees/lesson/Overview of the decision trees lesson: what you will learn, how it builds on logistic regression and sets up random forests, prerequisites, and time.Sun, 24 May 2026 00:00:00 GMTClawdemy11:00falseOverview of the decision trees lesson: what you will learn, how it builds on logistic regression and sets up random forests, prerequisites, and time.https://clawdemy.org/lessons/classical-machine-learning/fitting-a-line-linear-regression/lesson/https://clawdemy.org/lessons/classical-machine-learning/fitting-a-line-linear-regression/lesson/What the linear regression lesson covers, where it fits among classical machine learning methods, the prerequisites, and the time and difficulty.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseWhat the linear regression lesson covers, where it fits among classical machine learning methods, the prerequisites, and the time and difficulty.https://clawdemy.org/lessons/classical-machine-learning/hierarchical-clustering/lesson/https://clawdemy.org/lessons/classical-machine-learning/hierarchical-clustering/lesson/Orientation for the hierarchical clustering lesson: what a dendrogram is, the prerequisite, learning outcomes, and read and practice time.Sun, 24 May 2026 00:00:00 GMTClawdemy11:00falseOrientation for the hierarchical clustering lesson: what a dendrogram is, the prerequisite, learning outcomes, and read and practice time.https://clawdemy.org/lessons/classical-machine-learning/how-models-learn-gradient-descent/lesson/https://clawdemy.org/lessons/classical-machine-learning/how-models-learn-gradient-descent/lesson/A study guide to gradient descent: what it is, where it fits after linear regression, and the skills you will have by the end.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseA study guide to gradient descent: what it is, where it fits after linear regression, and the skills you will have by the end.https://clawdemy.org/lessons/classical-machine-learning/k-means-clustering/lesson/https://clawdemy.org/lessons/classical-machine-learning/k-means-clustering/lesson/An orientation to k-means clustering: what you will learn, where unsupervised learning fits, prerequisites, and the time and difficulty to expect.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseAn orientation to k-means clustering: what you will learn, where unsupervised learning fits, prerequisites, and the time and difficulty to expect.https://clawdemy.org/lessons/classical-machine-learning/logistic-regression/lesson/https://clawdemy.org/lessons/classical-machine-learning/logistic-regression/lesson/Overview of the logistic regression lesson: what you will learn, how it builds on linear regression and gradient descent, prerequisites, and time needed.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseOverview of the logistic regression lesson: what you will learn, how it builds on linear regression and gradient descent, prerequisites, and time needed.https://clawdemy.org/lessons/classical-machine-learning/random-forests/lesson/https://clawdemy.org/lessons/classical-machine-learning/random-forests/lesson/Brief for the random forests lesson: what you will learn, how forests fit after decision trees, prerequisites, and read time before you start.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseBrief for the random forests lesson: what you will learn, how forests fit after decision trees, prerequisites, and read time before you start.https://clawdemy.org/lessons/classical-machine-learning/support-vector-machines/lesson/https://clawdemy.org/lessons/classical-machine-learning/support-vector-machines/lesson/An orientation to support vector machines: what the maximum-margin idea and kernel trick teach, prerequisites, and the learning outcomes for this lesson.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseAn orientation to support vector machines: what the maximum-margin idea and kernel trick teach, prerequisites, and the learning outcomes for this lesson.https://clawdemy.org/lessons/classical-machine-learning/what-machine-learning-actually-is/lesson/https://clawdemy.org/lessons/classical-machine-learning/what-machine-learning-actually-is/lesson/What this opening lesson covers: the flip from rules to learning from data, the supervised and unsupervised families, and why models are judged on unseen data.Sun, 24 May 2026 00:00:00 GMTClawdemy10:00falseWhat this opening lesson covers: the flip from rules to learning from data, the supervised and unsupervised families, and why models are judged on unseen data.https://clawdemy.org/lessons/statistics-and-probability/bayes-theorem/lesson/https://clawdemy.org/lessons/statistics-and-probability/bayes-theorem/lesson/Overview of the Bayes' theorem lesson: what you will learn, prerequisites, the natural-frequencies and formula approach, and how it connects to AI.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseOverview of the Bayes' theorem lesson: what you will learn, prerequisites, the natural-frequencies and formula approach, and how it connects to AI.https://clawdemy.org/lessons/statistics-and-probability/conditional-probability-and-independence/lesson/https://clawdemy.org/lessons/statistics-and-probability/conditional-probability-and-independence/lesson/Overview of the conditional probability lesson: what you will learn, how it fits after the multiplication rule, the prerequisites, and the math involved.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseOverview of the conditional probability lesson: what you will learn, how it fits after the multiplication rule, the prerequisites, and the math involved.https://clawdemy.org/lessons/statistics-and-probability/confidence-intervals/lesson/https://clawdemy.org/lessons/statistics-and-probability/confidence-intervals/lesson/An overview of the confidence interval lesson: how to build the interval, what sets its width, the correct interpretation, and how to read AI metrics with it.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseAn overview of the confidence interval lesson: how to build the interval, what sets its width, the correct interpretation, and how to read AI metrics with it.https://clawdemy.org/lessons/statistics-and-probability/hypothesis-testing-and-p-values/lesson/https://clawdemy.org/lessons/statistics-and-probability/hypothesis-testing-and-p-values/lesson/An orientation to the hypothesis testing lesson: the null and alternative, the p-value, prerequisites, and the misreadings that make p so abused.Sun, 24 May 2026 00:00:00 GMTClawdemy13:00falseAn orientation to the hypothesis testing lesson: the null and alternative, the p-value, prerequisites, and the misreadings that make p so abused.https://clawdemy.org/lessons/statistics-and-probability/probability-foundations/lesson/https://clawdemy.org/lessons/statistics-and-probability/probability-foundations/lesson/An orientation to the probability lesson: what you will learn, where it fits in the track, prerequisites, and the math and time to expect before you start.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseAn orientation to the probability lesson: what you will learn, where it fits in the track, prerequisites, and the math and time to expect before you start.https://clawdemy.org/lessons/statistics-and-probability/random-variables-and-expected-value/lesson/https://clawdemy.org/lessons/statistics-and-probability/random-variables-and-expected-value/lesson/Preview of the random variables and expected value lesson: scope, prerequisites, the arithmetic involved, and how expected value underpins machine learning.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falsePreview of the random variables and expected value lesson: scope, prerequisites, the arithmetic involved, and how expected value underpins machine learning.https://clawdemy.org/lessons/statistics-and-probability/sampling-and-the-central-limit-theorem/lesson/https://clawdemy.org/lessons/statistics-and-probability/sampling-and-the-central-limit-theorem/lesson/Overview of the sampling and central limit theorem lesson: what it covers, the prerequisites, the light math, and the skills you will build before you start.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseOverview of the sampling and central limit theorem lesson: what it covers, the prerequisites, the light math, and the skills you will build before you start.https://clawdemy.org/lessons/statistics-and-probability/statistics-in-machine-learning/lesson/https://clawdemy.org/lessons/statistics-and-probability/statistics-in-machine-learning/lesson/How the capstone maps statistics tools onto an ML project, tests a model claim with four questions, and bounds where the statistical-thinking layer ends.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseHow the capstone maps statistics tools onto an ML project, tests a model claim with four questions, and bounds where the statistical-thinking layer ends.https://clawdemy.org/lessons/statistics-and-probability/summarizing-data-center-and-spread/lesson/https://clawdemy.org/lessons/statistics-and-probability/summarizing-data-center-and-spread/lesson/An orientation to summarizing data before modeling: the two questions every summary answers, prerequisites, the math involved, and what the lesson covers.Sun, 24 May 2026 00:00:00 GMTClawdemy11:00falseAn orientation to summarizing data before modeling: the two questions every summary answers, prerequisites, the math involved, and what the lesson covers.https://clawdemy.org/lessons/statistics-and-probability/the-binomial-distribution/lesson/https://clawdemy.org/lessons/statistics-and-probability/the-binomial-distribution/lesson/An orientation to the binomial distribution: what you will learn, how it builds on expected value, the math involved, and the time and difficulty to expect.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseAn orientation to the binomial distribution: what you will learn, how it builds on expected value, the math involved, and the time and difficulty to expect.https://clawdemy.org/lessons/statistics-and-probability/the-normal-distribution/lesson/https://clawdemy.org/lessons/statistics-and-probability/the-normal-distribution/lesson/A tour of the normal distribution lesson: what it covers, where it fits, prerequisites, the light arithmetic, and the AI connections.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseA tour of the normal distribution lesson: what it covers, where it fits, prerequisites, the light arithmetic, and the AI connections.https://clawdemy.org/lessons/statistics-and-probability/the-shape-of-data-distributions-and-histograms/lesson/https://clawdemy.org/lessons/statistics-and-probability/the-shape-of-data-distributions-and-histograms/lesson/Overview of the histogram lesson: what you will learn, where it fits after center and spread, the prerequisites, and why reading the shape of data matters.Sun, 24 May 2026 00:00:00 GMTClawdemy11:00falseOverview of the histogram lesson: what you will learn, where it fits after center and spread, the prerequisites, and why reading the shape of data matters.https://clawdemy.org/lessons/statistics-and-probability/when-two-things-move-together-correlation/lesson/https://clawdemy.org/lessons/statistics-and-probability/when-two-things-move-together-correlation/lesson/A preview of the correlation lesson: reading scatterplots, the correlation coefficient, the linear-only limit, correlation versus causation, and ML links.Sun, 24 May 2026 00:00:00 GMTClawdemy11:00falseA preview of the correlation lesson: reading scatterplots, the correlation coefficient, the linear-only limit, correlation versus causation, and ML links.https://clawdemy.org/lessons/statistics-and-probability/why-ai-runs-on-statistics/lesson/https://clawdemy.org/lessons/statistics-and-probability/why-ai-runs-on-statistics/lesson/What the opening statistics-for-AI lesson covers and why it comes first: the probability-statistics split, the track map, prerequisites, and time.Sun, 24 May 2026 00:00:00 GMTClawdemy10:00falseWhat the opening statistics-for-AI lesson covers and why it comes first: the probability-statistics split, the track map, prerequisites, and time.https://clawdemy.org/lessons/visual-math-calculus/chain-rule-visually/lesson/https://clawdemy.org/lessons/visual-math-calculus/chain-rule-visually/lesson/Overview of the chain rule: what nested functions are, why rates multiply through a composition, the evaluated-at gotcha, and the link to backpropagation.Sun, 24 May 2026 00:00:00 GMTClawdemy11:00falseOverview of the chain rule: what nested functions are, why rates multiply through a composition, the evaluated-at gotcha, and the link to backpropagation.https://clawdemy.org/lessons/visual-math-calculus/essence-of-calculus/lesson/https://clawdemy.org/lessons/visual-math-calculus/essence-of-calculus/lesson/A guided overview of the circle-area derivation: learning outcomes, where it fits in the track, prerequisites (none), and time and difficulty.Sun, 24 May 2026 00:00:00 GMTClawdemy10:00falseA guided overview of the circle-area derivation: learning outcomes, where it fits in the track, prerequisites (none), and time and difficulty.https://clawdemy.org/lessons/visual-math-calculus/implicit-differentiation/lesson/https://clawdemy.org/lessons/visual-math-calculus/implicit-differentiation/lesson/A guide to implicit differentiation: what it builds, where it fits after the chain rule, prerequisites, and the learning outcomes before you start.Sun, 24 May 2026 00:00:00 GMTClawdemy11:00falseA guide to implicit differentiation: what it builds, where it fits after the chain rule, prerequisites, and the learning outcomes before you start.https://clawdemy.org/lessons/visual-math-calculus/integration-and-the-fundamental-theorem/lesson/https://clawdemy.org/lessons/visual-math-calculus/integration-and-the-fundamental-theorem/lesson/What the integration lesson covers: the definite integral as Riemann sums, the fundamental theorem, antiderivatives reversed, plus prerequisites and timing.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseWhat the integration lesson covers: the definite integral as Riemann sums, the fundamental theorem, antiderivatives reversed, plus prerequisites and timing.https://clawdemy.org/lessons/visual-math-calculus/limits-done-carefully/lesson/https://clawdemy.org/lessons/visual-math-calculus/limits-done-carefully/lesson/Overview of the limit concept, the plain-English epsilon-delta idea, and L'Hopital's rule for 0/0 and infinity/infinity forms, with worked examples.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseOverview of the limit concept, the plain-English epsilon-delta idea, and L'Hopital's rule for 0/0 and infinity/infinity forms, with worked examples.https://clawdemy.org/lessons/visual-math-calculus/power-rule-from-geometry/lesson/https://clawdemy.org/lessons/visual-math-calculus/power-rule-from-geometry/lesson/What the power rule lesson covers: deriving d/dt(t^n) = n*t^(n-1) from growing squares and cubes, prerequisites, learning outcomes, and the time needed.Sun, 24 May 2026 00:00:00 GMTClawdemy11:00falseWhat the power rule lesson covers: deriving d/dt(t^n) = n*t^(n-1) from growing squares and cubes, prerequisites, learning outcomes, and the time needed.https://clawdemy.org/lessons/visual-math-calculus/product-rule-visually/lesson/https://clawdemy.org/lessons/visual-math-calculus/product-rule-visually/lesson/An overview of the product rule: why multiplying two derivatives is wrong, how a growing rectangle gives its two terms, plus the examples you will work.Sun, 24 May 2026 00:00:00 GMTClawdemy11:00falseAn overview of the product rule: why multiplying two derivatives is wrong, how a growing rectangle gives its two terms, plus the examples you will work.https://clawdemy.org/lessons/visual-math-calculus/the-derivative-as-a-rate/lesson/https://clawdemy.org/lessons/visual-math-calculus/the-derivative-as-a-rate/lesson/Brief overview of the derivative lesson: the instantaneous-rate paradox, the rise-over-run limit, free-fall velocity, and the secant-to-tangent picture.Sun, 24 May 2026 00:00:00 GMTClawdemy10:00falseBrief overview of the derivative lesson: the instantaneous-rate paradox, the rise-over-run limit, free-fall velocity, and the secant-to-tangent picture.https://clawdemy.org/lessons/visual-math-calculus/trig-derivatives-from-geometry/lesson/https://clawdemy.org/lessons/visual-math-calculus/trig-derivatives-from-geometry/lesson/A roadmap to deriving sine and cosine derivatives from a point on the unit circle: what you'll learn, prerequisites, and where it fits.Sun, 24 May 2026 00:00:00 GMTClawdemy11:00falseA roadmap to deriving sine and cosine derivatives from a point on the unit circle: what you'll learn, prerequisites, and where it fits.https://clawdemy.org/lessons/visual-math-calculus/why-area-equals-slope/lesson/https://clawdemy.org/lessons/visual-math-calculus/why-area-equals-slope/lesson/A guided overview of proving why area equals slope: the area function, the sliver argument giving A'(x)=f(x), and how it yields the fundamental theorem.Sun, 24 May 2026 00:00:00 GMTClawdemy11:00falseA guided overview of proving why area equals slope: the area function, the sliver argument giving A'(x)=f(x), and how it yields the fundamental theorem.https://clawdemy.org/lessons/visual-math-calculus/why-e-is-special/lesson/https://clawdemy.org/lessons/visual-math-calculus/why-e-is-special/lesson/An overview of why e^x is its own derivative: the multiplier crossing point, the chain-rule extension to e^(kx), and where e appears in growth and AI.Sun, 24 May 2026 00:00:00 GMTClawdemy11:00falseAn overview of why e^x is its own derivative: the multiplier crossing point, the chain-rule extension to e^(kx), and where e appears in growth and AI.https://clawdemy.org/lessons/visual-math-linear-algebra/3d-cross-product-via-duality/lesson/https://clawdemy.org/lessons/visual-math-linear-algebra/3d-cross-product-via-duality/lesson/Overview of the lesson that derives the 3D cross product from duality, with prerequisites, learning outcomes, and the three geometric properties it covers.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseOverview of the lesson that derives the 3D cross product from duality, with prerequisites, learning outcomes, and the three geometric properties it covers.https://clawdemy.org/lessons/visual-math-linear-algebra/3d-transformations/lesson/https://clawdemy.org/lessons/visual-math-linear-algebra/3d-transformations/lesson/Overview of the 3D linear algebra lesson: what you will learn, prerequisites, and how stepping into three dimensions sets up the determinant next.Sun, 24 May 2026 00:00:00 GMTClawdemy10:00falseOverview of the 3D linear algebra lesson: what you will learn, prerequisites, and how stepping into three dimensions sets up the determinant next.https://clawdemy.org/lessons/visual-math-linear-algebra/abstract-vector-spaces/lesson/https://clawdemy.org/lessons/visual-math-linear-algebra/abstract-vector-spaces/lesson/What this brief covers: functions and polynomials as vectors, the derivative as a matrix, prerequisites, time, and how every track tool generalizes.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseWhat this brief covers: functions and polynomials as vectors, the derivative as a matrix, prerequisites, time, and how every track tool generalizes.https://clawdemy.org/lessons/visual-math-linear-algebra/change-of-basis/lesson/https://clawdemy.org/lessons/visual-math-linear-algebra/change-of-basis/lesson/Overview of the change of basis lesson: what you'll learn, the prerequisites (inverses, transformations), and how it sets up eigenvectors.Sun, 24 May 2026 00:00:00 GMTClawdemy12:00falseOverview of the change of basis lesson: what you'll learn, the prerequisites (inverses, transformations), and how it sets up eigenvectors.https://clawdemy.org/lessons/visual-math-linear-algebra/cramers-rule/lesson/https://clawdemy.org/lessons/visual-math-linear-algebra/cramers-rule/lesson/A roadmap to the Cramer's rule lesson: prerequisites, the area-ratio derivation you will build, and what solving a 2x2 system as a determinant ratio covers.Sun, 24 May 2026 00:00:00 GMTClawdemy11:00falseA roadmap to the Cramer's rule lesson: prerequisites, the area-ratio derivation you will build, and what solving a 2x2 system as a determinant ratio covers.https://clawdemy.org/lessons/visual-math-linear-algebra/cross-products/lesson/https://clawdemy.org/lessons/visual-math-linear-algebra/cross-products/lesson/A brief on the 2D cross product: compute the signed area two vectors span, read its sign as orientation, and see it as the determinant you know.Sun, 24 May 2026 00:00:00 GMTClawdemy9:00falseA brief on the 2D cross product: compute the signed area two vectors span, read its sign as orientation, and see it as the determinant you know.https://clawdemy.org/lessons/visual-math-linear-algebra/determinant/lesson/https://clawdemy.org/lessons/visual-math-linear-algebra/determinant/lesson/A guide to the determinant: what it scales, how to read it off the unit square, the ad-bc formula, why zero means collapse, and the product rule.Sun, 24 May 2026 00:00:00 GMTClawdemy10:00falseA guide to the determinant: what it scales, how to read it off the unit square, the ad-bc formula, why zero means collapse, and the product rule.https://clawdemy.org/lessons/visual-math-linear-algebra/dot-products/lesson/https://clawdemy.org/lessons/visual-math-linear-algebra/dot-products/lesson/A learning guide to the dot product: the two formulas, projection, duality, and its role in attention and cosine similarity, plus prerequisites and timing.Sun, 24 May 2026 00:00:00 GMTClawdemy11:00falseA learning guide to the dot product: the two formulas, projection, duality, and its role in attention and cosine similarity, plus prerequisites and timing.https://clawdemy.org/lessons/visual-math-linear-algebra/eigenvectors-and-eigenvalues/lesson/https://clawdemy.org/lessons/visual-math-linear-algebra/eigenvectors-and-eigenvalues/lesson/Overview of the eigenvectors lesson: what you will learn, how diagonalization delivers the change-of-basis payoff, prerequisites, and time and difficulty.Sun, 24 May 2026 00:00:00 GMTClawdemy13:00falseOverview of the eigenvectors lesson: what you will learn, how diagonalization delivers the change-of-basis payoff, prerequisites, and time and difficulty.https://clawdemy.org/lessons/visual-math-linear-algebra/inverses-column-space-null-space/lesson/https://clawdemy.org/lessons/visual-math-linear-algebra/inverses-column-space-null-space/lesson/Orientation to inverses, column space, and null space: what you will learn, prerequisites, and the three equivalent tests for whether a matrix is invertible.Sun, 24 May 2026 00:00:00 GMTClawdemy11:00falseOrientation to inverses, column space, and null space: what you will learn, prerequisites, and the three equivalent tests for whether a matrix is invertible.https://clawdemy.org/lessons/visual-math-linear-algebra/linear-transformations/lesson/https://clawdemy.org/lessons/visual-math-linear-algebra/linear-transformations/lesson/What this lesson on linear transformations covers: a matrix as the record of where basis vectors land, plus prerequisites, timing, and outcomes.Sun, 24 May 2026 00:00:00 GMTClawdemy10:00falseWhat this lesson on linear transformations covers: a matrix as the record of where basis vectors land, plus prerequisites, timing, and outcomes.https://clawdemy.org/lessons/visual-math-linear-algebra/matrix-multiplication/lesson/https://clawdemy.org/lessons/visual-math-linear-algebra/matrix-multiplication/lesson/Overview of the matrix multiplication lesson: composition of transformations, computing products column by column, prerequisites, time, and outcomes.Sun, 24 May 2026 00:00:00 GMTClawdemy10:00falseOverview of the matrix multiplication lesson: composition of transformations, computing products column by column, prerequisites, time, and outcomes.https://clawdemy.org/lessons/visual-math-linear-algebra/nonsquare-matrices/lesson/https://clawdemy.org/lessons/visual-math-linear-algebra/nonsquare-matrices/lesson/Overview of rectangular matrices: read a shape to find input and output dimensions, tell embeddings from projections, and place column space and null space.Sun, 24 May 2026 00:00:00 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