In this video, we will understand why gradients.
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This clip is from the chapter "Deep learning: Recurrent Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this...

In this video, we will cover equations exercise.
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This clip is from the chapter "Deep learning: Recurrent Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and Projects) A to Z".In this...

In this video, we will cover implementation in NumPy BackwardPass 3.
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This clip is from the chapter "Deep learning: Convolutional Neural Networks with Python" of the series "Data Science and Machine Learning (Theory and...

In this video, we will cover Seaborn Heatmaps.
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This clip is from the chapter "Basics for Data Science: Data Understanding and Data Visualization with Python" of the series "Data Science and Machine Learning (Theory and...

In this video, we will cover a positive semi definite matrix.
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This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and Machine Learning...

In this video, we will cover Lagrange Multipliers.
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This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and Machine Learning (Theory and...

In this video, we will cover an introduction to mathematical foundation of feature selection.
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This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data...

In this video, we will cover activity-linear algebra module Python.
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This clip is from the chapter "Machine Learning: Feature Engineering and Dimensionality Reduction with Python" of the series "Data Science and Machine...

Dear linear algebra students, This is what matrices (and matrix manipulation) really look like

MATLAB is used to solve a set of linear equations (Ax=b) by inverting the matrix A and multiplying by the b vector. Three ways to solve A*x=b are:

x = inv(A)*b %
good
x = A\b
% better
x = linsol
SeeA,b) %...

It defines the transpose of a matrix. Further it states properties of transpose of a matrix.

It introduces and explains different types of matrices with examples.

It defines symmetric and skew symmetric matrices and states important theorems based on it.

An overview of the types of matrices and how to perform matrix addition.

An introduction to vector spaces.

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...

Chances are, you have heard the word “matrices” in a movie. But do you know what they are or what they are used for? Well, “matrices” is plural of a “matrix”. And you can think about a matrix as just a table of numbers, and that’s...

Defining basis and dimension.

How do perform Gauss-Jordan elimination.

How to multiply matrices.

In our previous video, we have seen what matrices are and how we label them. However, in order to use them efficiently, we must first be able to carry out simple operations with them, which is what we will be exploring in this video.

Defining complex matrices, hermitian matrices, and unitary matrices.

An introduction to inverse matrices.

An introduction to matrices and matrix notation