Linear Algebra

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Linear Algebra II: Matrix Algebra (edX)

This course takes you through roughly three weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology. Your ability to apply the concepts that we introduced in our previous course is enhanced when you can perform algebraic operations with matrices. [...]

Linear Algebra I: Linear Equations (edX)

This course takes you through the first three weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology. Systems of equations live at the heart of linear algebra. In this course you will explore fundamental concepts by exploring definitions and [...]

Linear Algebra IV: Orthogonality & Symmetric Matrices and the SVD (edX)

This course takes you through roughly five weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology. In the first part of this course you will explore methods to compute an approximate solution to an inconsistent system of equations that [...]

Linear Algebra III: Determinants and Eigenvalues (edX)

This course takes you through roughly three weeks of MATH 1554, Linear Algebra, as taught in the School of Mathematics at The Georgia Institute of Technology. At the beginning of this course we introduce the determinant, which yields two important concepts that you will use in this course.

Linear Algebra II: Matrices and Linear Transformations (edX)

This course provides an overview of bachelor-level linear algebra. You will review all the concepts and practice and refresh the skills related to matrices and linear transformations. A strong foundation in mathematics is critical for success in all science and engineering disciplines. Whether you want to make a strong [...]

Linear Algebra I: Vectors and Linear Equations (edX)

This course provides an overview of bachelor-level linear algebra. You will review all the concepts and practice and refresh the skills related to vectors and linear equations. A strong foundation in mathematics is critical for success in all science and engineering disciplines. Whether you want to make a strong [...]

Linear Algebra for Machine Learning and Data Science (Coursera)

Jun 5th 2023
Linear Algebra for Machine Learning and Data Science (Coursera)
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After completing this course, learners will be able to: represent data as vectors and matrices and identify their properties using concepts of singularity, rank, and linear independence, etc.; apply common vector and matrix algebra operations like dot product, inverse, and determinants; express certain types of matrix operations as linear [...]

Build Regression, Classification, and Clustering Models (Coursera)

Jun 5th 2023
Build Regression, Classification, and Clustering Models (Coursera)
Course Auditing
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In most cases, the ultimate goal of a machine learning project is to produce a model. Models make decisions, predictions—anything that can help the business understand itself, its customers, and its environment better than a human could. Models are constructed using algorithms, and in the world of machine learning, [...]
Jun 5th 2023
Course Auditing
41.00 EUR/month

Advanced Machine Learning and Signal Processing (Coursera)

Jun 5th 2023
Advanced Machine Learning and Signal Processing (Coursera)
Course Auditing
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This course, Advanced Machine Learning and Signal Processing, is part of the IBM Advanced Data Science Specialization which IBM is currently creating and gives you easy access to the invaluable insights into Supervised and Unsupervised Machine Learning Models used by experts in many field relevant disciplines. We’ll learn about [...]

Mathematics for Machine Learning: PCA (Coursera)

This intermediate-level course introduces the mathematical foundations to derive Principal Component Analysis (PCA), a fundamental dimensionality reduction technique. We'll cover some basic statistics of data sets, such as mean values and variances, we'll compute distances and angles between vectors using inner products and derive orthogonal projections of data onto [...]