Calculus for Machine Learning and Data Science
Completed by Blaise Romano Ségal
March 2, 2024
26 hours (approximately)
Blaise Romano Ségal'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: Python Programming
- Category: Machine Learning Algorithms
- Category: Advanced Mathematics
- Category: Deep Learning
- Category: Model Optimization
- Category: Artificial Neural Networks
- Category: Derivatives
