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[FreeTutorials.Us] Udemy - Mathematical Foundation For Machine Learning and AI
- Date: 2026-03-21
- Size: 1.8 GB
- Files: 31
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1. Introduction/1. Introduction.mp4
28 MB
2. Linear Algebra/1. Scalars, Vectors, Matrices, and Tensors.mp4
216 MB
2. Linear Algebra/2. Vector and Matrix Norms.mp4
53 MB
2. Linear Algebra/3. Vectors, Matrices, and Tensors in Python.mp4
114 MB
2. Linear Algebra/3.1 Project 1 - Vectors, Matrices, and Tensors in Python.zip.zip
177 kB
2. Linear Algebra/4. Special Matrices and Vectors.mp4
121 MB
2. Linear Algebra/5. Eigenvalues and Eigenvectors.mp4
64 MB
2. Linear Algebra/6. Norms and Eigendecomposition.mp4
178 MB
2. Linear Algebra/6.1 Project 2 - Norms and Eigendecomposition.zip.zip
232 kB
3. Multivariate Calculus/1. Introduction to Derivatives.mp4
143 MB
3. Multivariate Calculus/2. Basics of Integration.mp4
53 MB
3. Multivariate Calculus/3. Gradients.mp4
77 MB
3. Multivariate Calculus/4. Gradient Visualization.mp4
106 MB
3. Multivariate Calculus/4.1 Project 1 - Gradient Visualization.zip.zip
513 kB
3. Multivariate Calculus/5. Optimization.mp4
233 MB
4. Probability Theory/1. Intro to Probability Theory.mp4
97 MB
4. Probability Theory/2. Probability Distributions.mp4
79 MB
4. Probability Theory/3. Expectation, Variance, and Covariance.mp4
55 MB
4. Probability Theory/4. Graphing Probability Distributions in R.mp4
90 MB
4. Probability Theory/4.1 Graphing Probability Distributions in R.zip.zip
1.1 kB
4. Probability Theory/5. Covariance Matrices in R.mp4
62 MB
4. Probability Theory/5.1 Covariance Matrices in R.zip.zip
787 B
5. Probaility Theory/1. Special Random Variables.mp4
71 MB
5. Probaility Theory/1.1 Special Random Variables.zip.zip
134 kB
5. Probaility Theory/2. Bonus Lecture More Interesting Stuff, Offers and Discounts.html
1.7 kB