Machine Learning Foundations: Calculus
1h 30mBeginner2023-03-07
Authors
Terezija Semenski
Software Developer, Mathematician, Writer, and Learner
Course details
Studying artificial intelligence and machine learning can be difficult enough, but what if you threw some calculus into the mix? It may sound daunting, but understanding the foundations of calculus can help you design and implement machine learning algorithms, and without a solid foundation in calculus your work in machine learning can quickly become overwhelming. In this course, Terezija Semenski teaches you functions, derivatives, integrals, and the foundations of multivariate calculus. If you struggle with calculus concepts and techniques used to design and implement ML algorithms, check out this course with Terezija for the knowledge to overcome those challenges.
Skills covered
Machine LearningPythonFoundationsData AnalysisArtificial Intelligence (AI)Data ScienceBusiness Analysis and StrategyBusiness Software and ToolsOpen Source
Concepts
Introduction
- Learn calculus foundation for machine learning
- What you should know
Introduction to Calculus
- Defining calculus
- Applications of calculus in ML
- Functions
- Limits
Derivatives and Differentiation
- Introduction to derivatives
- The derivative of a constant and the power rule
- The constant multiple rule
- The sum rule
- The product rule
- The quotient rule
- The chain rule
- The power rule on a function chain
Multivariate Calculus
- Partial derivatives
- Calculating partial derivatives
- Higher-order partial derivatives
- The chain rule for partial derivatives
Machine Learning Gradients
- Single-point regression gradient
- The partial derivatives of quadratic cost
- Connecting partial derivatives with backpropagation
- Finding minima and maxima
Introduction to Integral Calculus
- Defining integral calculus
- Integration rules
- Indefinite integrals
- Definite integrals
Conclusion
- Next steps