Udemy Math Linear Algebra for Data Science Machine Learning 2023 | BBF97A29640AD2272C34A44C224C56E7C1028CAC

Udemy Math Linear Algebra for Data Science Machine Learning 2023

Name	Udemy - Math 0-1 Linear Algebra for Data Science & Machine Learning (8.2023)	DOWNLOAD Copy Link Trouble downloading? see How To
Total Size	11.2 GB
Total Files	194
Last Seen	2025-07-18 00:26
Hash	BBF97A29640AD2272C34A44C224C56E7C1028CAC

/1. Introduction/
1. Introduction and Outline.mp4	48.5 MB
2. How to Succeed in this Course.mp4	43.2 MB
3. Where to Get the Code.mp4	23.1 MB
4. How to Take this Course.mp4	21.3 MB
1. Introduction and Outline.srt	13.5 KB
2. How to Succeed in this Course.srt	12.8 KB
3. Where to Get the Code.srt	5.3 KB
4. How to Take this Course.srt	2.8 KB
3.2 Github Link.html	0.1 KB
3.1 Code Link.html	0.1 KB
/2. Linear Systems Review/
4. Gaussian Elimination.mp4	240.1 MB
3. 3 Equations and 3 Unknowns.mp4	172.1 MB
2. 2 Equations and 2 Unknowns.mp4	140.0 MB
1. Lines and Planes.mp4	107.6 MB
6. Infinitely Many Solutions.mp4	86.5 MB
5. No Solutions.mp4	51.4 MB
8. Suggestion Box.mp4	29.9 MB
7. Review Summary.mp4	24.9 MB
4. Gaussian Elimination.srt	26.9 KB
3. 3 Equations and 3 Unknowns.srt	20.6 KB
2. 2 Equations and 2 Unknowns.srt	16.0 KB
1. Lines and Planes.srt	11.7 KB
6. Infinitely Many Solutions.srt	10.3 KB
7. Review Summary.srt	5.9 KB
5. No Solutions.srt	5.8 KB
8. Suggestion Box.srt	4.9 KB
/3. Vectors and Matrices/
9. What is a Matrix.mp4	292.2 MB
6. Application Neural Embeddings, Cosine Similarity (Optional).mp4	238.1 MB
1. What is a Vector.mp4	210.7 MB
11. Matrix Multiplication.mp4	196.8 MB
3. Dot Product.mp4	167.6 MB
13. Matrix-Vector Product.mp4	138.6 MB
2. Adding and Subtracting Vectors.mp4	121.4 MB
5. Dot Product Exercises in Python.mp4	120.6 MB
16. Outer Product.mp4	105.4 MB
4. Dot Product (pt 2).mp4	97.7 MB
18. Matrix Exercises in Python.mp4	96.8 MB
12. Properties of Matrix Multiplication.mp4	92.1 MB
7. Exercise Normalizing a Vector.mp4	83.2 MB
20. Vectors and Matrices Summary.mp4	81.1 MB
14. Application Neural Networks.mp4	79.2 MB
17. Application Replicating GPT-4 (Optional).mp4	76.2 MB
19. Linear Systems Revisited.mp4	61.9 MB
8. Exercise The Vector Normal to a Plane.mp4	52.1 MB
10. Matrix Addition and Scalar Multiplication.mp4	38.4 MB
15. Element-Wise Product.mp4	33.0 MB
9. What is a Matrix.srt	35.0 KB
18. Matrix Exercises in Python.srt	33.2 KB
6. Application Neural Embeddings, Cosine Similarity (Optional).srt	28.0 KB
1. What is a Vector.srt	25.4 KB
5. Dot Product Exercises in Python.srt	23.6 KB
11. Matrix Multiplication.srt	22.0 KB
3. Dot Product.srt	18.8 KB
20. Vectors and Matrices Summary.srt	16.3 KB
13. Matrix-Vector Product.srt	14.9 KB
2. Adding and Subtracting Vectors.srt	13.1 KB
16. Outer Product.srt	11.4 KB
4. Dot Product (pt 2).srt	11.1 KB
7. Exercise Normalizing a Vector.srt	9.8 KB
12. Properties of Matrix Multiplication.srt	9.4 KB
17. Application Replicating GPT-4 (Optional).srt	8.6 KB
14. Application Neural Networks.srt	8.3 KB
19. Linear Systems Revisited.srt	7.0 KB
8. Exercise The Vector Normal to a Plane.srt	5.6 KB
10. Matrix Addition and Scalar Multiplication.srt	4.3 KB
15. Element-Wise Product.srt	3.4 KB
/4. Matrix Operations and Special Matrices/
21. Positive Definite and Negative Definite Matrices.mp4	269.1 MB
16. Determinants (pt 2).mp4	267.2 MB
7. Properties of the Matrix Transpose.mp4	253.9 MB
3. Matrix Inverse.mp4	249.2 MB
23. Exercise Complete the Square.mp4	226.5 MB
6. Matrix Transpose.mp4	197.9 MB
15. Determinants (pt 1).mp4	197.9 MB
10. Orthogonal and Orthonormal Matrices and Vectors.mp4	149.0 MB
9. Transpose in Higher Dimensions.mp4	139.7 MB
17. Determinant Formula (Optional).mp4	124.1 MB
2. Diagonal Matrices.mp4	116.5 MB
14. Exercise Why Are Orthogonal Matrices Length- and Angle-Preserving.mp4	100.1 MB
24. Matrix Operations Exercises in Python.mp4	84.5 MB
5. Singular Matrices.mp4	83.0 MB
8. Symmetric Matrices.mp4	81.0 MB
20. Matrix Trace (Optional).mp4	79.9 MB
4. Exercise Inverse of the Inverse.mp4	77.1 MB
25. Matrix Operations and Special Matrices Summary.mp4	66.4 MB
1. Identity Matrix.mp4	60.2 MB
18. Determinant Identities (Optional).mp4	60.2 MB
22. Exercise Inverse of a Positive Definite Matrix.mp4	41.3 MB
13. Exercise Transpose of Inverse of Symmetric Matrix.mp4	40.0 MB
11. Exercise Orthogonal Matrices.mp4	33.0 MB
19. Exercise Determinant of a Unitary Matrix.mp4	24.5 MB
12. Exercise Inverse of a Product.mp4	23.7 MB
7. Properties of the Matrix Transpose.srt	34.5 KB
16. Determinants (pt 2).srt	28.1 KB
3. Matrix Inverse.srt	27.1 KB
21. Positive Definite and Negative Definite Matrices.srt	26.1 KB
23. Exercise Complete the Square.srt	25.1 KB
15. Determinants (pt 1).srt	23.1 KB
6. Matrix Transpose.srt	22.1 KB
24. Matrix Operations Exercises in Python.srt	18.9 KB
9. Transpose in Higher Dimensions.srt	16.9 KB
25. Matrix Operations and Special Matrices Summary.srt	16.6 KB
10. Orthogonal and Orthonormal Matrices and Vectors.srt	15.5 KB
17. Determinant Formula (Optional).srt	15.2 KB
14. Exercise Why Are Orthogonal Matrices Length- and Angle-Preserving.srt	11.1 KB
5. Singular Matrices.srt	9.5 KB
2. Diagonal Matrices.srt	9.3 KB
8. Symmetric Matrices.srt	8.8 KB
20. Matrix Trace (Optional).srt	8.6 KB
4. Exercise Inverse of the Inverse.srt	8.2 KB
18. Determinant Identities (Optional).srt	7.6 KB
1. Identity Matrix.srt	6.8 KB
13. Exercise Transpose of Inverse of Symmetric Matrix.srt	4.3 KB
22. Exercise Inverse of a Positive Definite Matrix.srt	4.2 KB
11. Exercise Orthogonal Matrices.srt	4.0 KB
12. Exercise Inverse of a Product.srt	2.5 KB
19. Exercise Determinant of a Unitary Matrix.srt	2.4 KB
/5. Matrix Rank/
1. Linear Independence and Dependence.mp4	376.3 MB
4. Matrix Decompositions (SVD, QR, LU, Cholesky).mp4	269.1 MB
5. Rank After Multplication.mp4	257.2 MB
3. The Rank of a Matrix.mp4	234.3 MB
7. Applications Recommender Systems and Topic Modeling (Optional).mp4	188.6 MB
6. Low-Rank Approximations and Frobenius Norm.mp4	140.0 MB
8. Applications of SVD Data Visualization and Feature Selection (Optional).mp4	133.9 MB
11. Matrix Decompositions in Python.mp4	117.5 MB
9. Application LoRA for Diffusion Models and LLMs (Optional).mp4	99.3 MB
2. Geometric Interpretation of Linear Combinations.mp4	85.9 MB
10. Exercise Generating a Positive Semi-Definite Matrix.mp4	58.4 MB
12. Matrix Rank Summary.mp4	32.8 MB
1. Linear Independence and Dependence.srt	38.9 KB
4. Matrix Decompositions (SVD, QR, LU, Cholesky).srt	26.6 KB
11. Matrix Decompositions in Python.srt	26.0 KB
5. Rank After Multplication.srt	24.7 KB
3. The Rank of a Matrix.srt	21.5 KB
7. Applications Recommender Systems and Topic Modeling (Optional).srt	18.7 KB
6. Low-Rank Approximations and Frobenius Norm.srt	13.6 KB
8. Applications of SVD Data Visualization and Feature Selection (Optional).srt	13.3 KB
9. Application LoRA for Diffusion Models and LLMs (Optional).srt	10.4 KB
2. Geometric Interpretation of Linear Combinations.srt	8.5 KB
12. Matrix Rank Summary.srt	6.9 KB
10. Exercise Generating a Positive Semi-Definite Matrix.srt	5.7 KB
/6. Eigenvalues and Eigenvectors/
13. Constructing the SVD (Proof of SVD).mp4	291.7 MB
12. Diagonalization.mp4	261.9 MB
1. How to Find Eigenvalues and Eigenvectors (pt 1).mp4	255.4 MB
3. Exercise Rotation Matrix.mp4	232.6 MB
17. Eigenvalues in Python.mp4	152.3 MB
16. Functions of Matrices (Optional).mp4	143.9 MB
6. Conjugate Transpose and Hermitian Matrices.mp4	119.5 MB
9. Test for Positive Definiteness Using Eigenvalues.mp4	91.1 MB
15. Application The Vanishing Gradient Problem.mp4	90.6 MB
14. Matrix Powers.mp4	86.4 MB
19. Eigenvalues and Eigenvectors Summary.mp4	74.5 MB
8. Why Do Hermitian Matrices Have Orthogonal Eigenvectors.mp4	67.4 MB
7. Hermitian Matrices Have Real Eigenvalues.mp4	64.9 MB
18. Quiz Square Root of a Matrix.mp4	58.1 MB
11. Invertibility From Eigenvalues (Positive Definite Matrices Are Invertible).mp4	48.7 MB
10. Determinant From Eigenvalues.mp4	30.6 MB
2. How to Find Eigenvalues and Eigenvectors (pt 2).mp4	28.5 MB
4. Exercise Why Do A^TA and AA^T Have the Same Eigenvalues.mp4	27.7 MB
5. Exercise Eigenvalues of the Inverse.mp4	26.6 MB
17. Eigenvalues in Python.srt	35.2 KB
1. How to Find Eigenvalues and Eigenvectors (pt 1).srt	26.6 KB
13. Constructing the SVD (Proof of SVD).srt	26.4 KB
12. Diagonalization.srt	25.8 KB
3. Exercise Rotation Matrix.srt	24.7 KB
19. Eigenvalues and Eigenvectors Summary.srt	15.8 KB
16. Functions of Matrices (Optional).srt	14.9 KB
6. Conjugate Transpose and Hermitian Matrices.srt	11.8 KB
15. Application The Vanishing Gradient Problem.srt	9.9 KB
14. Matrix Powers.srt	9.6 KB
9. Test for Positive Definiteness Using Eigenvalues.srt	8.5 KB
7. Hermitian Matrices Have Real Eigenvalues.srt	7.7 KB
8. Why Do Hermitian Matrices Have Orthogonal Eigenvectors.srt	7.0 KB
18. Quiz Square Root of a Matrix.srt	6.3 KB
11. Invertibility From Eigenvalues (Positive Definite Matrices Are Invertible).srt	5.3 KB
2. How to Find Eigenvalues and Eigenvectors (pt 2).srt	3.4 KB
4. Exercise Why Do A^TA and AA^T Have the Same Eigenvalues.srt	3.2 KB
10. Determinant From Eigenvalues.srt	3.0 KB
5. Exercise Eigenvalues of the Inverse.srt	2.7 KB
/7. Setting Up Your Environment (AppendixFAQ by Student Request)/
2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.mp4	154.3 MB
1. Anaconda Environment Setup.mp4	55.2 MB
1. Anaconda Environment Setup.srt	20.6 KB
2. How to install Numpy, Scipy, Matplotlib, Pandas, IPython, Theano, and TensorFlow.srt	16.2 KB
/8. Effective Learning Strategies (AppendixFAQ by Student Request)/
4. What order should I take your courses in (part 2).mp4	111.0 MB
1. Can YouTube Teach Me Calculus.mp4	91.1 MB
3. What order should I take your courses in (part 1).mp4	81.7 MB
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.mp4	40.4 MB
2. Is this for Beginners or Experts Academic or Practical Fast or slow-paced.srt	33.3 KB
1. Can YouTube Teach Me Calculus.srt	25.5 KB
4. What order should I take your courses in (part 2).srt	24.5 KB
3. What order should I take your courses in (part 1).srt	17.1 KB
/9. Appendix FAQ Finale/
2. BONUS.mp4	41.9 MB
1. What is the Appendix.mp4	17.0 MB
2. BONUS.srt	8.1 KB
1. What is the Appendix.srt	3.8 KB
Total files 194