Calculus for Machine Learning and Data Science
Completed by Sayhan Yalvaçer
March 19, 2024
26 hours (approximately)
Sayhan Yalvaçer'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: Computer Programming
- Category: Deep Learning
- Category: Machine Learning
- Category: Applied Mathematics
- Category: Applied Machine Learning
- Category: Machine Learning Methods
- Category: Python Programming
- Category: Calculus
- Category: Artificial Neural Networks
- Category: Model Optimization
- Category: Mathematical Modeling
- Category: Data Visualization
