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| 0. (1Hack.Us) Premium Tutorials-Guides-Articles & Community based Forum.url |
377б |
| 1. (FreeTutorials.Us) Download Udemy Paid Courses For Free.url |
328б |
| 1.1 Special Random Variables.zip.zip |
133.48Кб |
| 1. Introduction.mp4 |
27.82Мб |
| 1. Introduction to Derivatives.mp4 |
143.30Мб |
| 1. Intro to Probability Theory.mp4 |
96.82Мб |
| 1. Scalars, Vectors, Matrices, and Tensors.mp4 |
215.45Мб |
| 1. Special Random Variables.mp4 |
71.40Мб |
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| 2. Basics of Integration.mp4 |
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| 2. Probability Distributions.mp4 |
79.19Мб |
| 2. Vector and Matrix Norms.mp4 |
53.15Мб |
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| 3.1 Project 1 - Vectors, Matrices, and Tensors in Python.zip.zip |
176.59Кб |
| 3. Expectation, Variance, and Covariance.mp4 |
55.42Мб |
| 3. Gradients.mp4 |
76.84Мб |
| 3. Vectors, Matrices, and Tensors in Python.mp4 |
114.03Мб |
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| 4.1 Graphing Probability Distributions in R.zip.zip |
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| 4.1 Project 1 - Gradient Visualization.zip.zip |
513.00Кб |
| 4. Gradient Visualization.mp4 |
105.46Мб |
| 4. Graphing Probability Distributions in R.mp4 |
90.49Мб |
| 4. Special Matrices and Vectors.mp4 |
121.07Мб |
| 5.1 Covariance Matrices in R.zip.zip |
787б |
| 5. Covariance Matrices in R.mp4 |
61.69Мб |
| 5. Eigenvalues and Eigenvectors.mp4 |
64.29Мб |
| 5. Optimization.mp4 |
233.06Мб |
| 6.1 Project 2 - Norms and Eigendecomposition.zip.zip |
232.01Кб |
| 6. Norms and Eigendecomposition.mp4 |
177.86Мб |
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237б |