Linear algebra is the backbone of deep learning. This course provides a fundamental understanding of vectors, matrices, and their operations, which are essential for building and optimizing complex machine learning models.
Overview
Syllabus
- Lesson 1: Basics of Vectors and Matrices
- Vectors and Matrices in Python
- Modify the Column Vector
- Fix the Matrix
- Defining the Matrix
- Find the Dimensions of a Matrix
- Creating a 3D Matrix from Two 2x2 Matrices
- Lesson 2: Basic Vector Operations
- Calculate Weekly Total Sales Using Vector Addition
- Predicting Expenses with Inflation and Scalar Multiplication
- Perform Price Adjustments on Product List
- Combine Student Scores Using Vector Addition
- Lesson 3: Basic Matrix Operations
- Total Sales Calculation per Product Using Matrix Addition
- Adjust Monthly Budgets by Percentage Increase
- Calculating Average Daily Temperatures
- Exploring the Transposition
- Lesson 4: Dot Product and Matrix Multiplication
- Calculating Dot Product of Forces in 3D Space
- Change Vectors to Achieve Zero Dot Product
- Check If Matrix Multiplication Is Possible and Compute the Result
- Matrix-Vector Multiplication
- Lesson 5: Determinant and Linear Dependency
- Calculate Determinant and Check for Linear Dependency
- Define a Matrix with Zero Determinant
- Find the Determinant of a 3x3 Matrix
- Solvability Check Using Determinants
