Calculus for Machine Learning and Data Science
Completed by Felipe Díaz Jaramillo
September 20, 2024
26 hours (approximately)
Felipe Díaz Jaramillo'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: Applied Machine Learning
- Category: Applied Mathematics
- Category: Machine Learning
- Category: Machine Learning Algorithms
- Category: Computer Programming
- Category: Software Visualization
- Category: Machine Learning Methods
- Category: Derivatives
- Category: Advanced Mathematics
- Category: Calculus
- Category: Python Programming
- Category: Numerical Analysis
