Calculus for Machine Learning and Data Science
Completed by Andrew Berezhniuk
February 12, 2024
26 hours (approximately)
Andrew Berezhniuk'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: Data Visualization
- Category: Machine Learning Methods
- Category: Applied Mathematics
- Category: Python Programming
- Category: Machine Learning Software
- Category: Calculus
- Category: Computer Programming
- Category: Applied Machine Learning
- Category: Derivatives
- Category: Deep Learning
- Category: Numerical Analysis
- Category: Artificial Neural Networks
