Calculus for Machine Learning and Data Science
Completed by Vladimir Nedashkovskiy
October 19, 2024
26 hours (approximately)
Vladimir Nedashkovskiy'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 Algorithms
- Category: Python Programming
- Category: Applied Machine Learning
- Category: Model Optimization
- Category: Deep Learning
- Category: Artificial Neural Networks
- Category: Numerical Analysis
- Category: Software Visualization
- Category: Machine Learning Methods
- Category: Applied Mathematics
- Category: Calculus
- Category: Advanced Mathematics
