Calculus Essentials for Machine Learning
Explore the world of calculus with a focus on its essential applications in machine learning. This course builds on foundational calculus concepts, introducing intermediate learners to more complex techniques vital for understanding and developing machine learning models. Explore derivatives, integrals, and optimization techniques that form the backbone of algorithms and data-driven solutions.
What You'll Learn
Derivatives in Machine Learning
Understand how derivatives are used to optimize machine learning models.
Integrals and Probability
Learn the application of integrals in calculating probabilities and expected values.
Multivariable Calculus
Explore functions of several variables and their importance in machine learning.
Optimization Techniques
Gain insights into optimization techniques such as gradient descent.
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