Calculus for Machine Learning and Data Science
Completed by Neil Yejjey
January 27, 2024
26 hours (approximately)
Neil Yejjey'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: Applied Machine Learning
- Category: Machine Learning Algorithms
- Category: Machine Learning Methods
- Category: Software Visualization
- Category: Applied Mathematics
- Category: Artificial Neural Networks
- Category: Model Optimization
- Category: Python Programming
- Category: Deep Learning
- Category: Numerical Analysis
- Category: Advanced Mathematics
- Category: Computer Programming
