Calculus for Machine Learning and Data Science
Completed by Daniel Lachner Piza
October 23, 2024
26 hours (approximately)
Daniel Lachner Piza'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: Derivatives
- Category: Applied Mathematics
- Category: Mathematical Modeling
- Category: Data Visualization
- Category: Computer Programming
- Category: Numerical Analysis
- Category: Model Optimization
- Category: Calculus
- Category: Artificial Neural Networks
- Category: Applied Machine Learning
- Category: Python Programming
- Category: Machine Learning Methods
