part derivatives

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1. 1▶Lecture 5 Part 1: Derivative of Matrix Determinant and InverseMIT 18.S096 Matrix Calculus For Machine Learning And Beyond, IAP 2023Notes
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2. 2▶Lecture 5 Part 2: Forward Automatic Differentiation via Dual NumbersMIT 18.S096 Matrix Calculus For Machine Learning And Beyond, IAP 2023Notes
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3. 3▶Lecture 5 Part 3: Differentiation on Computational GraphsMIT 18.S096 Matrix Calculus For Machine Learning And Beyond, IAP 2023Notes
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4. 4▶Lecture 1 Part 1: Introduction and MotivationMIT 18.S096 Matrix Calculus For Machine Learning And Beyond, IAP 2023Notes
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5. 5▶Lecture 3 Part 1: Kronecker Products and JacobiansMIT 18.S096 Matrix Calculus For Machine Learning And Beyond, IAP 2023Notes
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6. 6▶Lecture 3 Part 2: Finite-Difference ApproximationsMIT 18.S096 Matrix Calculus For Machine Learning And Beyond, IAP 2023Notes
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7. 7▶Lecture 2 Part 1: Derivatives in Higher Dimensions: Jacobians and Matrix FunctionsMIT 18.S096 Matrix Calculus For Machine Learning And Beyond, IAP 2023Notes
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8. 8▶Lecture 4 Part 2: Nonlinear Root Finding, Optimization, and Adjoint Gradient MethodsMIT 18.S096 Matrix Calculus For Machine Learning And Beyond, IAP 2023Notes
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9. 9▶Lecture 7 Part 2: Second Derivatives, Bilinear Forms, and Hessian MatricesMIT 18.S096 Matrix Calculus For Machine Learning And Beyond, IAP 2023Notes
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10. 10▶Lecture 4 Part 1: Gradients and Inner Products in Other Vector SpacesMIT 18.S096 Matrix Calculus For Machine Learning And Beyond, IAP 2023Notes
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