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- Session Overview
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Classroom Contents
Essential Mathematics Behind AI: From Linear Algebra to Neural Networks
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- 1 - Session Overview
- 2 - Role of Mathematics in AI
- 3 - The Importance of Mathematics in AI Models
- 4 - Linear Algebra: Patterns into Matrices
- 5 - Calculus: Optimizing Models for Accuracy
- 6 - Plotting Data and Identifying Patterns
- 7 - Slope and Intercept of a Line
- 8 - Gradients and Their Role in AI
- 9 - Calculating Derivatives for Curved Lines
- 10 - Gradient Descent: Minimizing Cost Functions
- 11 - Vectors and Their Role in AI
- 12 - Matrices: Representing Data in AI
- 13 - Transforming Text into Numerical Representations
- 14 - Word Embeddings and Semantic Relationships
- 15 - Applications and Tools
