fft algorithm
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Advice for Applying Machine Learning, Debugging Reinforcement Learning (RL) Algorithm, Linear Quadratic Regularization (LQR), Differential Dynamic Programming (DDP), Kalman Filter & Linear Quadratic Gaussian (LQG), Predict/update Steps of Kalman Filter, Linear Quadratic Gaussian (LQG)
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Joint Space Dynamics, Newton-Euler Algorithm, Inertia Tensor, Example, Newton-Euler Equations, Lagrange Equations, Equations of Motion
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The Concept of Unsupervised Learning, K-means Clustering Algorithm, K-means Algorithm, Mixtures of Gaussians and the EM Algorithm, Jensen's Inequality, The EM Algorithm, Summary
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Selection Sort, Live Demo: Working/execution of the Code, Selection Sort Analysis, Insertion Sort Algorithm, Live Demo: Working/execution of Insertion Sort, Insertion Sort Analysis, Insertion vs Selection, Quadratic Growth of the Algorithm, Merge Sort, Merge Sort: Working/execution Demo, Merge Sort Code Explanation, Merge Sort Analysis, Quadratic vs Linear Arithmetic, Sort 'Race', Quick Sort Idea
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Handout Information, Section Sign-up, Karel Commands, An Algorithm vs Program, Syntax of a Karel Program, Running a Karel Program, Creating Methods, SuperKarel, A for Loop, A While Loop, Karel Conditions, If Statement, Putting it All Together
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Writing a Recursive Power Set Function in Scheme, Using a Lambda Mapping Function that Cons-Es the Car to Every Element in the Power-Set of the Cdr to Make the Recursive Step in the Power-Set Function, Using a Let Binding to Cause Power-Set to Only Make One Recursive Call Rather than Two, Structure of a Let Binding, How Expressions Within a Let Binding Cannot Depend On Each Other Unless the Let* Keyword Is Used, How a Let Binding Is Compil...more
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Note: This course is being offered this summer by Stanford as an online course for credit. It can be taken individually, or as part of a master’s degree or graduate certificate earned online through the Stanford Center for Professional Development. The goals for the course are to gain a facility with using the Fourier transform, both specific techniques and general principles, and learning to recognize when, why, and how it is used. To...more
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Kernels, Mercer's Theorem, Non-linear Decision Boundaries and Soft Margin SVM, Coordinate Ascent Algorithm, The Sequential Minimization Optimization (SMO) Algorithm, Applications of SVM
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The Factor Analysis Model,0 EM for Factor Analysis, Principal Component Analysis (PCA), PCA as a Dimensionality Reduction Algorithm, Applications of PCA, Face Recognition by Using PCA
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Bayesian Statistics and Regularization, Online Learning, Advice for Applying Machine Learning Algorithms, Debugging/fixing Learning Algorithms, Diagnostics for Bias & Variance, Optimization Algorithm Diagnostics, Diagnostic Example - Autonomous Helicopter, Error Analysis, Getting Started on a Learning Problem
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Latent Semantic Indexing (LSI), Singular Value Decomposition (SVD) Implementation, Independent Component Analysis (ICA), The Application of ICA, Cumulative Distribution Function (CDF), ICA Algorithm, The Applications of ICA
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Algorithm Analysis, Evaluating the Performance, Analysis of Codes: Statement Counts, Another Example (Statement Count Contd.), Comparing Algorithm, Big-O Notation, Big-O to Predict the Time of Execution, Best/Worst/Average Case, Analysis of Recursive Algorithms, Another Example : Towers of Hanoi, A Tabulation for Different Algorithms, Growth Patterns, Application of Algorithm Analysis to Sorting, Selection Sort, Selection Sort Code
