├── .gitignore ├── 01-Linear_Algebra ├── Week_01 │ ├── 01-Solving some simultaneous equations.png │ ├── 01-Solving some simultaneous equations.txt │ ├── 02-Exploring parameter space.png │ ├── 02-Exploring parameter space.txt │ ├── 03-Doing some vector operations.png │ └── 03-Doing some vector operations.txt ├── Week_02 │ ├── 01-Dot product of vectors.png │ ├── 01-Dot product of vectors.txt │ ├── 02-Changing basis.png │ ├── 02-Changing basis.txt │ ├── 03-Linear dependency of a set of vectors.png │ ├── 03-Linear dependency of a set of vectors.txt │ ├── 04-Vector operations assessment.png │ └── 04-Vector operations assessment.txt ├── Week_03 │ ├── 01-Using matrices to make transformations.png │ ├── 01-Using matrices to make transformations.txt │ ├── 02-Solving linear equations using the inverse matrix.png │ ├── 02-Solving linear equations using the inverse matrix.txt │ └── notebooks │ │ └── IdentifyingSpecialMatrices.ipynb ├── Week_04 │ ├── 01-Non-square matrix multiplication.png │ ├── 01-Non-square matrix multiplication.txt │ ├── 02-Mappings to spaces with different numbers of dimensions.png │ ├── 02-Mappings to spaces with different numbers of dimensions.txt │ └── notebooks │ │ ├── GramSchmidtProcess (SOLVED).ipynb │ │ ├── GramSchmidtProcess.ipynb │ │ ├── ReflectingBear (SOLVED).ipynb │ │ ├── ReflectingBear.ipynb │ │ └── readonly │ │ └── bearNecessities.py └── Week_05 │ ├── 01-Selecting eigenvectors by inspection.png │ ├── 01-Selecting eigenvectors by inspection.txt │ ├── 02-Characteristic polynomials, eigenvalues and eigenvectors.png │ ├── 02-Characteristic polynomials, eigenvalues and eigenvectors.txt │ ├── 03-Diagonalisation and applications.png │ ├── 03-Diagonalisation and applications.txt │ ├── 04-Eigenvalues and eigenvectors.png │ ├── 04-Eigenvalues and eigenvectors.txt │ └── notebooks │ ├── PageRank (SOLVED).ipynb │ ├── PageRank.ipynb │ └── readonly │ ├── PageRankFunctions.py │ ├── internet.png │ └── internet2.png ├── 02-Multivariate_Calculus ├── Week_01 │ ├── 01-Matching functions visually.png │ ├── 01-Matching functions visually.txt │ ├── 02-Matching the graph of a function to the graph of its derivative.png │ ├── 02-Matching the graph of a function to the graph of its derivative.txt │ ├── 03-Let's differentiate some functions.png │ ├── 03-Let's differentiate some functions.txt │ ├── 04-Practicing the product rule.png │ ├── 04-Practicing the product rule.txt │ ├── 05-Practicing the chain rule.png │ ├── 05-Practicing the chain rule.txt │ ├── 06-Unleashing the toolbox.png │ └── 06-Unleashing the toolbox.txt ├── Week_02 │ ├── 01-Practicing partial differentiation.png │ ├── 01-Practicing partial differentiation.txt │ ├── 02-Calculating the Jacobian.png │ ├── 02-Calculating the Jacobian.txt │ ├── 03-Bigger Jacobians!.png │ ├── 03-Bigger Jacobians!.txt │ ├── 04-Calculating Hessians.png │ ├── 04-Calculating Hessians.txt │ ├── 05-Jacobians and Hessians.png │ └── 05-Jacobians and Hessians.txt ├── Week_03 │ ├── 01-Multivariate chain rule exercise.png │ ├── 01-Multivariate chain rule exercise.txt │ ├── 02-Simple Artificial Neural Networks.png │ ├── 02-Simple Artificial Neural Networks.txt │ ├── 03-Training Neural Networks.png │ ├── 03-Training Neural Networks.txt │ └── notebooks │ │ ├── Backpropagation (SOLVED).ipynb │ │ ├── Backpropagation.ipynb │ │ └── readonly │ │ ├── BackpropModule.ipynb │ │ └── bigNet.png ├── Week_04 │ ├── 01-Matching functions and approximations.png │ ├── 01-Matching functions and approximations.txt │ ├── 02-Applying the Taylor series.png │ ├── 02-Applying the Taylor series.txt │ ├── 03-Taylor series - Special cases.png │ ├── 03-Taylor series - Special cases.txt │ ├── 04-2D Taylor series.png │ ├── 04-2D Taylor series.txt │ ├── 05-Taylor Series Assessment.png │ └── 05-Taylor Series Assessment.txt ├── Week_05 │ ├── 01-Newton-Raphson in one dimension.png │ ├── 01-Newton-Raphson in one dimension.txt │ ├── 02-Checking Newton-Raphson.png │ ├── 02-Checking Newton-Raphson.txt │ ├── 03-Lagrange multipliers.png │ ├── 03-Lagrange multipliers.txt │ ├── 04-Optimisation scenarios.png │ └── 04-Optimisation scenarios.txt └── Week_06 │ ├── 01-Linear regression.png │ ├── 01-Linear regression.txt │ ├── 02-Fitting a non-linear function.png │ ├── 02-Fitting a non-linear function.txt │ └── notebooks │ ├── Fitting the distribution of heights data (SOLVED).ipynb │ ├── Fitting the distribution of heights data.ipynb │ └── readonly │ └── HeightsModule.py ├── 03-PCA ├── Week_01 │ ├── 01-Mean of datasets.png │ ├── 01-Mean of datasets.txt │ ├── 02-Variance of 1D datasets.png │ ├── 02-Variance of 1D datasets.txt │ ├── 03-Covariance matrix of a two-dimensional dataset.png │ ├── 03-Covariance matrix of a two-dimensional dataset.txt │ └── notebooks │ │ ├── numpy_tutorial.ipynb │ │ ├── week1 (SOLVED).ipynb │ │ └── week1.ipynb ├── Week_02 │ ├── 01-Dot product.png │ ├── 01-Dot product.txt │ ├── 02-Properties of inner products.png │ ├── 02-Properties of inner products.txt │ ├── 03-General inner products lengths and distances.png │ ├── 03-General inner products lengths and distances.txt │ ├── 04-Angles between vectors using a non-standard inner product.png │ ├── 04-Angles between vectors using a non-standard inner product.txt │ ├── README.md │ └── notebooks │ │ ├── load_data.py │ │ ├── week2 (SOLVED).ipynb │ │ └── week2.ipynb ├── Week_03 │ ├── 01-Projection onto a 1-dimensional subspace.png │ ├── 01-Projection onto a 1-dimensional subspace.txt │ ├── 02-Project 3D data onto a 2D subspace.png │ ├── 02-Project 3D data onto a 2D subspace.txt │ └── notebooks │ │ ├── eigenfaces.npy │ │ ├── olivetti_py3.pkz │ │ ├── week3 (SOLVED).ipynb │ │ └── week3.ipynb └── Week_04 │ ├── 01-Chain rule practice.png │ ├── 01-Chain rule practice.txt │ ├── README.md │ └── notebooks │ ├── load_data.py │ ├── week4 (SOLVED).ipynb │ └── week4.ipynb └── README.md /.gitignore: -------------------------------------------------------------------------------- 1 | */mnist-original.mat 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