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Summary Understanding Deep Learning
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Uploaded on
08-05-2025
Written in
2024/2025
Understand deep learning with this comprehensive guide! Dive into essential topics like Linear Algebra, Probability, and Numerical Computation, crucial for mastering machine learning algorithms. Understand Scalars, Vectors, Matrices, Tensors, Eigen decomposition, and more. Explore Probability Distributions, Conditional Probability, and Bayes' Rule to build a strong foundation in data science. This document is your ultimate resource, packed with vital knowledge for beginners and professionals alike. Elevate your skills and stay ahead in the dynamic field of AI and deep learning by purchasing this must-have PDF today!
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Written for
- Module
- Deep Learning
All documents for this subject (12)
Document information
- Uploaded on
- May 8, 2025
- Number of pages
- 31
- Written in
- 2024/2025
- Type
- Summary
Subjects
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deep learning
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linear algebra
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scalars
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vectors
-
matrices
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matrix operations
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numerical computation
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covariance matrix
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variance
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stochastic ma
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singular value decomposition svd
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principal component analysis pca
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