Academic
  • Introduction
  • Artificial Intelligence
    • Introduction
    • AI Concepts, Terminology, and Application Areas
    • AI: Issues, Concerns and Ethical Considerations
  • Biology
    • Scientific Method
    • Chemistry of Life
    • Water, Acids, Bases
    • Properties of carbon
    • Macromolecules
    • Energy and Enzymes
    • Structure of a cell
    • Membranes and transport
    • Cellular respiration
    • Cell Signaling
    • Cell Division
    • Classical and molecular genetics
    • DNA as the genetic material
    • Central dogma
    • Gene regulation
  • Bioinformatics
    • Bioinformatics Overview
  • Deep Learning
    • Neural Networks and Deep Learning
      • Introduction
      • Logistic Regression as a Neural Network
      • Python and Vectorization
      • Shallow Neural Network
      • Deep Neural Network
    • Improving Deep Neural Networks
      • Setting up your Machine Learning Application
      • Regularizing your Neural Network
      • Setting up your Optimization Problem
      • Optimization algorithms
      • Hyperparameter, Batch Normalization, Softmax
    • Structuring Machine Learning Projects
    • Convolutional Neural Networks
      • Introduction
    • Sequence Models
      • Recurrent Neural Networks
      • Natural Language Processing & Word Embeddings
      • Sequence models & Attention mechanism
  • Linear Algebra
    • Vectors and Spaces
      • Vectors
      • Linear combinations and spans
      • Linear dependence and independence
      • Subspaces and the basis for a subspace
      • Vector dot and cross products
      • Matrices for solving systems by elimination
      • Null space and column space
    • Matrix transformations
      • Functions and linear transformations
      • Linear transformation examples
      • Transformations and matrix multiplication
      • Inverse functions and transformations
      • Finding inverses and determinants
      • More Determinant Depth
  • Machine Learning
    • Introduction
    • Linear Regression
      • Model and Cost Function
      • Parameter Learning
      • Multivariate Linear Regression
      • Computing Parameters Analytically
      • Octave
    • Logistic Regression
      • Classification and Representation
      • Logistic Regression Model
    • Regularization
      • Solving the Problem of Overfitting
    • Neural Networks
      • Introduction of Neural Networks
      • Neural Networks - Learning
    • Improve Learning Algorithm
      • Advice for Applying Machine Learning
      • Machine Learning System Design
    • Support Vector Machine
      • Large Margin Classification
      • Kernels
      • SVM in Practice
  • NCKU - Artificial Intelligence
    • Introduction
    • Intelligent Agents
    • Solving Problems by Searching
    • Beyond Classical Search
    • Learning from Examples
  • NCKU - Computer Architecture
    • First Week
  • NCKU - Data Mining
    • Introduction
    • Association Analysis
    • FP-growth
    • Other Association Rules
    • Sequence Pattern
    • Classification
    • Evaluation
    • Clustering
    • Link Analysis
  • NCKU - Machine Learning
    • Probability
    • Inference
    • Bayesian Inference
    • Introduction
  • NCKU - Robotic Navigation and Exploration
    • Kinetic Model & Vehicle Control
    • Motion Planning
    • SLAM Back-end (I)
    • SLAM Back-end (II)
    • Computer Vision / Multi-view Geometry
    • Lie group & Lie algebra
    • SLAM Front-end
  • Python
    • Numpy
    • Pandas
    • Scikit-learn
      • Introduction
      • Statistic Learning
  • Statstics
    • Quantitative Data
    • Modeling Data Distribution
    • Bivariate Numerical Data
    • Probability
    • Random Variables
    • Sampling Distribution
    • Confidence Intervals
    • Significance tests
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  1. Linear Algebra

Matrix transformations

Functions and linear transformationsLinear transformation examplesTransformations and matrix multiplicationInverse functions and transformationsFinding inverses and determinantsMore Determinant Depth
PreviousNull space and column spaceNextFunctions and linear transformations

Last updated 5 years ago

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