Calculus for Machine Learning and Data Science
Completed by matthew weaver
May 31, 2024
26 hours (approximately)
matthew weaver'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: Machine Learning Algorithms
- Category: Advanced Mathematics
- Category: Applied Machine Learning
- Category: Numerical Analysis
- Category: Calculus
- Category: Deep Learning
- Category: Model Optimization
- Category: Artificial Neural Networks
- Category: Derivatives
- Category: Software Visualization
