Search result for Matrix methods Online Courses & Certifications
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Matrix Methods
by Daniel Boley- 4.1
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Approx. 7 hours to complete
Mathematical Matrix Methods lie at the root of most methods of machine learning and data analysis of tabular data. Learn the basics of Matrix Methods, including matrix-matrix multiplication, solving linear equations, orthogonality, and best least squares approximation. Matrix Matrix Multiplication and other Operations Matrix as Mathematical Objects Matrix Transpose Supplement: Matrix Transpose in Python...
Numerical Methods for Engineers
by Jeffrey R. Chasnov- 4.9
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Approx. 40 hours to complete
Numerical Methods for Engineers covers the most important numerical methods that an engineer should know. We derive basic algorithms in root finding, matrix algebra, integration and interpolation, ordinary and partial differential equations. Runge-Kutta Methods | Lecture 50 Second-Order Runge-Kutta Methods | Lecture 51 Higher-Order Runge-Kutta Methods | Lecture 52 Runge-Kutta Methods and Quadrature Formulas...
First Steps in Linear Algebra for Machine Learning
by Dmitri Piontkovski , Vsevolod L. Chernyshev- 4.1
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Approx. 21 hours to complete
Another goal is to improve the student’s practical skills of using linear algebra methods in machine learning and data analysis. Matrix arithmetics Properties of matrix operations and some special matrices Matrix inverse The Inverse matrix with Gaussian elimination Covered Python methods Matrix arithmetics Matrix inverse The Inverse matrix with Gaussian elimination...
Machine Learning
by John W. Paisley- 0.0
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12 Weeks
Topics include: classification and regression, clustering methods, sequential models, matrix factorization, topic modeling and model selection. We will discuss several fundamental methods for performing this task and algorithms for their optimization. We will cover three fundamental problems of unsupervised learning: data clustering, matrix factorization, and sequential models for order-dependent data....
$249
Linear Algebra IV: Orthogonality & Symmetric Matrices and the SVD
by Greg Mayer- 0.0
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3 Weeks
In the first part of this course you will explore methods to compute an approximate solution to an inconsistent system of equations that have no solutions. Construct the QR factorization of a matrix Characterize properties of a matrix using its QR decomposition Construct an orthogonal diagonalization of a symmetric matrix Construct a spectral decomposition of a matrix...
$199
Introduction to numerical analysis
by Evgeni Burovski- 4.7
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Approx. 18 hours to complete
LU decomposition: the matrix form of the Gaussian elimination. Matrix norms. Common matrix norms. Canonic form of two-step iterative methods for linear systems....
Complete linear algebra: theory and implementation in code
by Mike X Cohen- 4.8
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33.5 hours on-demand video
Learn concepts in linear algebra and matrix analysis, and implement them in MATLAB and Python. Beginning to intermediate topics, including vectors, matrix multiplications, least-squares projections, eigendecomposition, and singular-value decomposition. Strong focus on modern applications-oriented aspects of linear algebra and matrix analysis....
$13.99
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The Complete MATLAB Mastery - From a Beginner to an Expert
by Tod Vachev- 4.5
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10 hours on-demand video
Everything in our world today can be viewed as some kind of a matrix, and I’m not talking about the Matrix Trilogy. How to handle The Matrix: It is not necessary to look for the red pill, like Neo had to – what you actually need is MATLAB, which means MATrix LABoratory contrary to popular belief....
$16.99
Visual Perception for Self-Driving Cars
by Steven Waslander- 4.7
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Approx. 31 hours to complete
This course will introduce you to the main perception tasks in autonomous driving, static and dynamic object detection, and will survey common computer vision methods for robotic perception. You'll apply these methods to visual odometry, object detection and tracking, and semantic segmentation for drivable surface estimation. Apply these methods to visual odometry, object detection and tracking...
PCA & multivariate signal processing, applied to neural data
by Mike X Cohen- 4.7
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10 hours on-demand video
The purpose of this course is to teach you some matrix-based data analysis methods in neural time series data, with a focus on multivariate dimensionality reduction and source-separation methods. mathematician, engineer, or physicist who is curious about applied matrix decompositions in neuroscience....
$11.99
