Calculus for Machine Learning and Data Science
Completed by Agustín Fernández Chávez
June 25, 2024
26 hours (approximately)
Agustín Fernández Chávez'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: Deep Learning
- Category: Artificial Neural Networks
- Category: Model Optimization
- Category: Advanced Mathematics
- Category: Derivatives
- Category: Numerical Analysis
- Category: Calculus
- Category: Python Programming
- Category: Applied Mathematics
- Category: Machine Learning
- Category: Machine Learning Algorithms
- Category: Computer Programming
