Calculus for Machine Learning and Data Science
Completed by Ernie Clevenger
January 12, 2024
26 hours (approximately)
Ernie Clevenger'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: Machine Learning
- Category: Computer Programming
- Category: Software Visualization
- Category: Applied Mathematics
- Category: Applied Machine Learning
- Category: Machine Learning Algorithms
- Category: Advanced Mathematics
- Category: Python Programming
- Category: Derivatives
- Category: Calculus
- Category: Model Optimization
- Category: Deep Learning
