Calculus for Machine Learning and Data Science

Updated for 2024! Mathematics for Machine Learning and Data Science is an online foundational program created by DeepLearning.AI and taught by Luis Serrano. In machine learning, you apply mathematical concepts through programming. And in this specialization, you will apply the mathematical concepts you learn using Python programming in hands-on labs. To succeed in this program, you will need basic to intermediate Python programming skills. After completing this course, students will be able to: - Analytically optimize various types of functions used in machine learning using properties of derivatives and gradients - Approximately optimize various types of functions used in machine learning using first-order (gradient descent) and second-order (Newton's method) iterative methods - Visually interpret differentiation of various types of functions used in machine learning - Perform gradient descent on neural networks with different activation and cost functions Many machine learning engineers and data scientists need help with mathematics, and even seasoned practitioners can feel held back by a lack of mathematical skills. This specialization uses innovative pedagogy in mathematics to help you learn quickly and intuitively, with courses that use simple visualizations to help you see how the mathematics behind machine learning actually works. We recommend that you have a high school level of math (functions, basic algebra) and familiarity with programming (data structures, loops, functions, conditionals, debugging). The assignments and labs are written in Python, but the course covers all the machine learning libraries you will use.