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) Applied Optimization Problems
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Classroom Contents
Calculus for Beginners - Calculus for Machine Learning
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- 1 ) A Preview of Calculus
- 2 ) The Limit of a Function.
- 3 ) The Limit Laws
- 4 ) Continuity
- 5 ) The Precise Definition of a Limit
- 6 ) Defining the Derivative
- 7 ) The Derivative as a Function
- 8 ) Differentiation Rules
- 9 ) Derivatives as Rates of Change
- 10 ) Derivatives of Trigonometric Functions
- 11 ) The Chain Rule
- 12 ) Derivatives of Inverse Functions
- 13 ) Implicit Differentiation
- 14 ) Derivatives of Exponential and Logarithmic Functions
- 15 ) Partial Derivatives
- 16 ) Related Rates
- 17 ) Linear Approximations and Differentials
- 18 ) Maxima and Minima
- 19 ) The Mean Value Theorem
- 20 ) Derivatives and the Shape of a Graph
- 21 ) Limits at Infinity and Asymptotes
- 22 ) Applied Optimization Problems
- 23 ) L'Hopital's Rule
- 24 ) Newton's Method
- 25 ) Antiderivatives
