Calculus for Machine Learning and Data Science
Completed by Giancarlo Segovia Quispe
January 28, 2024
26 hours (approximately)
Giancarlo Segovia Quispe'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: Software Visualization
- Category: Machine Learning Methods
- Category: Applied Mathematics
- Category: Python Programming
- Category: Machine Learning Algorithms
- Category: Applied Machine Learning
- Category: Numerical Analysis
- Category: Advanced Mathematics
- Category: Computer Programming
