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* D003x.1 Applications of Linear Algebra (Part 1)

Unit 1: Entering the Matrix

  1. Gain an overview perspective of applications of linear algebra
  2. Be able to distinguish between linear and nonlinear equations
  3. Learn terminology of related to matrices
  4. Learn an algorithm that uses a matrix to visually approximate an image using ASCII characters.

Online app to create ASCII images

Introduction to Unit 1 (01:44)

1.1 - When Life is Linear (04:08)

will gain an appreciation for how linear processes can model or approximation the world. We will also look specifically at wireframe models that create 3D models.

1.1 Exploratory Activity: When Life is Linear (03:17)

1.2 Being 1 Dimensional (11:29)

1.3.1 Matrix Magic (06:39)

1.3.2 Activity: Build Your Own Matrix (03:42)

1.4.1 Spying Submatrices (05:58)

1.4.2 Spying Submatrices: Activity (05:42)

1.5.1 ASCII Art (07;24)

Activity Overview: Create Your Own ASCII Art (05:26)

In this unit, you will learn the following:

  1. To compute matrix addition
  2. To compute scalar multiplication
  3. To compute a convex combination of matrices
  4. Image manipulation using matrix arithmetic

online app for Inversion online online app to Combine pictures online app to generate blending gifs make animation from gif images sequence

Introduction to Unit 2 (02;23)

2.1.1 Get Inverted (07:48)

2.1.2 Exploratory Activity: Get Inverted (06:04)

2.2.1 Take the Combo (04:37)

To combine two images with matrix arithmetic αA+(1-α)B

2.2.2 Activity: Blended Photos

2.3.1 Fade Away (06;23)

to adapt the ideas of the last section to create an animation.

2.3.2 Activity Overview: Creating Animated GIFS

In this unit, you will learn the following:

  1. To compute the Euclidean norm on vectors
  2. To compute the taxicab norm on vectors
  3. An application of vector norms to data mining for movie recommendations
  4. An application of vector norms to reading handwritten numbers

a dataset of movie ratings

Introduction to Unit 3 (01:18)

The Norm in Movies (13:11)

  • How to compute the Euclidean norm
  • How to compute the taxicab norm
  • How to apply vector norms to data mining in the context of a movie recommendation system

Activity: Finding Similar Movies (03:38)

Reading the mail -Fitting the Norm (05:28)

  • How to apply vector norms to compare images
  • An algorithm for identify handwritten digits

Activity: Learning Where Algorithms Work and Don’t Work (02:11)

Unit 4: Go Forth and Multiply

  • To multiply two vectors
  • To find the dot product between two vectors
  • To find the angle between two vectors
  • An application of the dot product to data mining for movie recommendations
  • To multiply two matrices
  • When multiplication cannot be performed between two matrices
  • How to rotate, translate, and reflect points with matrix multiplication
  • Applications of matrix multiplication to image creation and manipulation

Spinograph application Transformation

Introduction to Unit 4 (01:34)

Scaly Byproduct

How to multiply two vectors How to compute the dot product of two vectors How to find the angle between two vectors How to apply the dot product to data mining in the context of a movie recommendation system

Activity: Finding Similar Movies (Again, But Different) (03:37)

Spinning Out With Multiplication (06:16)

How to multiply two matrices When two matrices cannot be multiplied How to use matrix multiplication to rotate a point about the origin A way to create an image by rotating points with matrix multiplication How to apply vector norms to data mining in the context of a movie recommendation system

Activity: Creating Spirographs With Linear Algebra (02:09)

Seeing Double: Symmetry (10:30)

How to convert a Cartesian coordinate to a homogeneous coordinate (x,y) = (u*x,u*y,u) (1,3) = (1,3,1) (1,3) = (2,6,2) How to convert a homogeneous coordinate to a Cartesian coordinate How to rotate, translate, and reflect homogeneous coordinates with matrix multiplication An application of rotation, translation and reflection to the artwork of puzzle master Scott Kim

Activity: Linear Transformations

Unit 5: It’s Elementary

To solve a system of linear equations The three elementary row operations used to solve linear systems An application of two of the elementary row operations to image manipulation Two encryption methods that utilize linear algebra

Introduction and Learning Goals

5.1 Getting Eliminated (04:55)

How matrix methods date back to 200 BC How to solve systems of linear equations

Seeing Diagon-alley(07:49)

There are 3 operations that allow us to move from one lineas system to another. The three elementary row operations used to solve a linear system.
  1. Switch any 2 rows
  2. multiply any row with non-zero scalar
  3. replacing a row by the sum of a non-zero scalar multiple of that row and another row.

An application of two of the elementary row operations to image manipulation

Activity: Gaussian Elimination (05:04)

http://math365.org/lifeislinear/Flip/Flip.html http://math365.org/lifeislinear/RowMult/RowMult.html

Being Cryptic

Activity: Shifting to the Cryptic

http://math365.org/lifeislinear/CaesarDecode/CaesarDecode.html

5.4 Deciphering Linear Systems

  • A method of encryption that uses matrices
  • The inverse of a matrix and how to use it to solve linear systems

Activity Overview: Encoding

Unit 6: Sports Ranking March MATHness

Introduction to Unit 6

6.1 Catching the Madness

6.2 Who’s Number 1? Sports Ranking

6.3 March MATHness

6.3 Exploratory Activity

Unit 7: Least Squares

Introduction and Learning Goals

7.1 Dash of Math

7.1 Exploratory Activity: John Brenkus Sports Question

End of Course Survey

More Resources

The Tech Museum

Pixar: Tony DeRose

Unit 1: Math To The Max – Least-Squares

Unit 1 Introduction

1.1 Dash of Math

1.1 Exploratory Activity

1.2 Presidential Look-Alike

1.2 Exploratory Activity

1.3 Getting Correlated

1.3 Exploratory Activity

Unit 2: Time To Stretch – Eigenvectors

Unit 3: Zombie Math – Decomposing

Unit 4: What Are The Chances?

Unit 5: Mining For Meaning

Unit 6: Sports Ranking