Multivariable calculus, class #10: chain rule for vector-valued functions, directional derivatives
Mathematician spotlight: David Rockoff We do an example of the chain rule for vector-valued functions, where the Jacobian matrix is a product of the Jacobian matrix of derivatives for each function. Then we introduce the directional derivative, and give the meaning of the direction of the gradient.
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Multivariable calculus, class #11: directional derivative, gradient, tangent lines & tangent planes
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Multivariable calculus, class #6: partial derivatives and tangent planes
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Multivariable calculus, class #5: multivariable limits
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Geometric Meaning of the Gradient Vector
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Total differentials and the chain rule | MIT 18.02SC Multivariable Calculus, Fall 2010
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Multivariable calculus, Class #1 - lines, planes and cross product
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General relativity from first principles – Adam Brown
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Multivariable calculus, class #7: Differentiability of multivariable functions
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Best Explanation of Maxwell's Equations
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Jacobian and Chain Rule
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Multivariable calculus, Class #3 - New coordinate systems
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Turing Award Winner: Disagreeing with Google, Postgres, Future Problems | Mike Stonebraker
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The Hardest Questions in Physics | World Science Festival
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No Boss, No Money: The Raw Reality of China’s Gen-Z Freelancers
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Multivariable calculus, class #40: Summary of the course
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From Child Prodigy to Winning Fields Medal, Nobel of Math
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The Multi-Variable Chain Rule: Derivatives of Compositions
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The derivative of x^x: Multivariable chain rule (matrix version)
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