Machine Learning Foundations Linear Algebra

Machine Learning Foundations Linear Algebra

with Terezija Semenski
Electronic Video - 2022

Explore the fundamentals of linear algebra, the mathematical foundation of machine learning algorithms.

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Détails bibliographiques
Collectivité auteur: linkedin.com (Firm)
Autres auteurs: Semenski, Terezija (Intervenant)
Format: Électronique Vidéo
Langue:English
Publié: Carpenteria, CA linkedin.com, 2022.
Sujets:
Accès en ligne:View course details on linkedin.com/learning

MARC

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520 |a Explore the fundamentals of linear algebra, the mathematical foundation of machine learning algorithms. 
511 1 |a Presenter: Terezija Semenski 
520 |a Ever wondered what’s really going on underneath a machine learning algorithm? The answer is linear algebra. Without it, machine learning can’t exist. Linear algebra is a prerequisite for understanding and creating nearly all machine learning algorithms, especially those that prop up neural networks, natural language processing tools, and deep learning models. Join instructor Terezija Semenski for an in-depth exploration of the core concepts of linear algebra alongside the techniques needed to design and implement a successful machine learning algorithm. Discover the basics of vector arithmetic, vector norms, matrix properties, advanced operations, matrix transformation, and algorithms like Google PageRank. By the end of this course, you’ll be ready to take the principles of linear algebra and apply them to your next big machine learning project. 
538 |a Latest version of the following browsers: Chrome, Safari, Firefox, or Internet Explorer. Adobe Flash Player Plugin. JavaScript and cookies must be enabled. A broadband Internet connection. 
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