Calculus for Machine Learning and Data Science
Completed by Jin Wook Shin
May 11, 2024
26 hours (approximately)
Jin Wook Shin'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: Python Programming
- Category: Machine Learning Algorithms
- Category: Applied Machine Learning
- Category: Machine Learning
- Category: Computer Programming
- Category: Advanced Mathematics
- Category: Derivatives
- Category: Artificial Neural Networks
- Category: Model Optimization
- Category: Calculus
- Category: Software Visualization
- Category: Machine Learning Methods
