Home > Search Results

linear algebra


sort by: Relevancy | Title try advanced search for more options

  1. Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language.

  2. Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language.

  3. Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language.

  4. Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language.

  5. 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

  6. After discussing the statistical basis of the law of mass action, the lecture turns to developing a framework for understanding reaction rates. A potential energy surface that associates energy with polyatomic geometry can be realized physically for a linear, triatomic system, but it is more practical to use collective energies for starting material, transition state, and product, together with Eyring theory, to predict rates. Free-radical...more

  7. An Application of Supervised Learning - Autonomous Deriving, ALVINN, Linear Regression, Gradient Descent, Batch Gradient Descent, Stochastic Gradient Descent (Incremental Descent), Matrix Derivative Notation for Deriving Normal Equations, Derivation of Normal Equations

  8. Heat, conductivity, and thermal expansion are the discussed in this lecture. Both linear thermal expansion, leading to a need for expansion joints in railroad rails on hot days, and cubical thermal expansion, as occurs in a mercury thermometer, are covered in detail. The lectures ends with a focus on the cubical thermal expansion of water: the density of ice is about 8% lower than water, so ice cubes and icebergs float.

  9. The Concept of Underfitting and Overfitting, The Concept of Parametric Algorithms and Non-parametric Algorithms, Locally Weighted Regression, The Probabilistic Interpretation of Linear Regression, The motivation of Logistic Regression, Logistic Regression, Perceptron

  10. This lecture covers resistive forces such as air drag. It includes the viscous (linear in velocity) and pressure (quadratic in velocity) terms. Quantitative demonstrations with balloons and with ball bearings dropped in syrup are shown. He concludes with numerical calculations of air drag examples, also discussing the contribution of air drag to the quantitative experiments down earlier in the course with falling apples.

  11. Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language.

  12. Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language.