What are the Applications of Linear Algebra and Calculus in Machine Learning?

  • Thread starter Brandon Trabucco
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In summary, linear algebra and calculus are fundamental mathematical tools used in machine learning for data analysis, prediction, and optimization. Linear algebra is used to represent and manipulate data in the form of vectors and matrices, while calculus is used to find the optimal solutions and parameters for machine learning models. These techniques are crucial in various applications of machine learning such as image and speech recognition, natural language processing, and recommendation systems. They also play a vital role in deep learning, where complex neural networks are trained using gradient descent algorithms based on calculus. Overall, linear algebra and calculus are essential for understanding and developing advanced machine learning algorithms and applications.
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Brandon Trabucco
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Hello, my name is Brandon Trabucco. Junior in high school, I have a deep fascination with logical and mathematical relationships. I am a self taught programmer and musician and I dream to attend college at MIT when I graduate. It is a pleasure to meet all of you, and I look forward to discussing mathematics with all of you.
 
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  • #3
Hello and thank you. The area of math that interest me most is not math by itself, but rather the application of linear algebra and differential and integral calculus to write machine learning algorithms for computers. The master algorithm is a great book that I have been able to find on this subject.

Reversing back to pure math, however, I am fascinated with complex numbers.
 

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