3Blue1Brown
Inverse matrices, column space and null space | Essence of linear algebra, chapter 7
How do you think about the column space and null space of a matrix visually? How do you think about the inverse of a matrix?
3Blue1Brown
Three-dimensional linear transformations | Essence of linear algebra, footnote
How to think of 3x3 matrices as transforming 3d space
3Blue1Brown
Three-dimensional linear transformations | Essence of linear algebra, chapter 5
How to think of 3x3 matrices as transforming 3d space
3Blue1Brown
Matrix multiplication as composition: Essence of Linear Algebra - Part 4 of 15
How to think about matrix multiplication visually as successively applying two different linear transformations.
3Blue1Brown
Linear transformations and matrices | Essence of linear algebra, chapter 3
When you think of matrices as transforming space, rather than as grids of numbers, so much of linear algebra starts to make sense.
3Blue1Brown
The determinant | Essence of linear algebra, chapter 6
The determinant has a very natural visual intuition, even though it's formula can make it seem more complicated than it really is.
Curated Video
Fundamentals of Neural Networks - Activation Function
This video explains the role of the activation function, which is an interesting phenomenon in the design of neural networks. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This...
Curated Video
Deep Learning - Artificial Neural Networks with Tensorflow - Making Predictions
In this video, we will be talking about another important part of creating a model, which is making predictions. This clip is from the chapter "Machine Learning and Neurons" of the series "Deep Learning - Artificial Neural Networks with...
Curated Video
Evaluate the impact of an AI application used in the real world. (case study) : Working with Flower Images: Case Study - Part 5
From the section: CNN-Industry Live Project: Playing With Real World Natural Images. This section includes a live project of working with flower images. CNN-Industry Live Project: Playing with Real World Natural Images: Working with...
Packt
Fundamentals of Neural Networks - Activation Function
This video explains the role of the activation function, which is an interesting phenomenon in the design of neural networks. This clip is from the chapter "Artificial Neural Networks" of the series "Fundamentals in Neural Networks".This...
Curated Video
Fundamentals of Machine Learning - Deep Learning
This video introduces you to deep learning, artificial neural networks, recurrent neural networks, and more. This clip is from the chapter "Lectures" of the series "Fundamentals of Machine Learning".This section explains the basics of...
Professor Dave Explains
Linear Transformations on Vector Spaces
How to perform linear transformations on vector spaces.
Looking Glass Universe
Matrices make sense: Linear transformations and matrix multiplication
Matrices are often presented as a useful bookkeeping/ commutation tools to students- but there's much more to them. When you understand what a Matrix really is so many parts of Linear Algebra will be completely obvious to you, including...
Khan Academy
Khan Academy: Linear Algebra: Exploring the Solution Set of Ax=b
Video first graphs the transformation image of a specific transformation. Then examines the solution set for a couple particular points in the image. Shows that the solution set is a shifted version of the null space. [16:34]
Khan Academy
Khan Academy: Linear Algebra: Compositions of Linear Transformations 2
Video shows that the transformation matrix of the composition of linear functions is the product of the transformation matrices of each linear transformation in the composition. [16:30]
Khan Academy
Khan Academy: Linear Algebra: Projection Onto a Subspace Is a Lin Transformation
A video lesson proving that any projection onto a subspace is actually a linear transformation. Also, if given the basis for the subspace then the specific transformation matrix for the projection can be found. Includes a brief...
Khan Academy
Khan Academy: Linear Algebra: Determining Whether a Transformation Is Onto
Video reviews from previous videos that a function is invertible if and only if it is onto and one-to-one. Shows how to determine if a linear transformation is onto by showing that the columns of the transformation matrix span the...
Khan Academy
Khan Academy: Linear Algebra: Compositions of Linear Transformations 1
Video first shows an intuitive sense of what composing linear transformations does and the notation used. Shows that the composition of linear transformations is also a linear transformation. [12:21]
Khan Academy
Khan Academy: Linear Algebra: Determinant as Scaling Factor
Video demonstrating that the area of a parallelogram that is the image of a rectangle under a transformation is equivalent to the absolute value of the determinant of the matrix whose column vectors generate the parallelogram. Includes...
Khan Academy
Khan Academy: Linear Algebra: Expressing Projection as Matrix Vector Product
Video shows how to simplify the vector projection formula using unit vectors. Shows that projections are linear transformations. Shows the general formula for the transformation matrix for projections in R^2. Shows an example using the...
Khan Academy
Khan Academy: Linear Algebra: Expressing Projection as Matrix Vector Product
Video shows how to simplify the vector projection formula using unit vectors. Shows that projections are linear transformations. Shows the general formula for the transformation matrix for projections in R^2. Shows an example using the...
Khan Academy
Khan Academy: Linear Algebra: Linear Transformation Examples: Rotations in R2
Video first shows visually that a rotation is a linear transformation. Shows how to construct a transformation matrix that will rotate a vector through a given angle. Shows both the general rotation matrix and an example of a rotation...
Khan Academy
Khan Academy: Linear Algebra: Image of a Subset Under a Transformation
Video shows an example of the image of a subset of a domain under a linear transformation. Example includes defining a triangle using vectors. [18:11]