Calculus for Machine Learning and Data Science
Completed by Axel Largent
November 18, 2024
26 hours (approximately)
Axel Largent's account is verified. Coursera certifies their successful completion of Calculus for Machine Learning and Data Science
What you will learn
Analytically optimize different types of functions commonly used in machine learning using properties of derivatives and gradients
Approximately optimize different types of functions commonly used in machine learning
Visually interpret differentiation of different types of functions commonly used in machine learning
Perform gradient descent in neural networks with different activation and cost functions
Skills you will gain
- Category: Python Programming
- Category: Software Visualization
- Category: Machine Learning Methods
- Category: Applied Mathematics
- Category: Machine Learning Algorithms
- Category: Numerical Analysis
- Category: Derivatives
- Category: Advanced Mathematics
- Category: Calculus
- Category: Applied Machine Learning
- Category: Computer Programming
- Category: Machine Learning
