Supervised Machine Learning: Regression and Classification

via Coursera

Overview

Embark on your journey into the world of artificial intelligence with the Machine Learning Specialization, a comprehensive online program designed to introduce you to the fundamentals of machine learning. This beginner-friendly specialization, a collaboration between DeepLearning.AI and Stanford Online, is expertly taught by AI pioneer Andrew Ng. Dive into building and training supervised machine learning models for real-world applications using Python, alongside renowned libraries like NumPy and scikit-learn.

Throughout this first course, you will focus on critical skills, including constructing machine learning models for both prediction and binary classification tasks. Explore various facets of supervised learning such as linear regression and logistic regression. This specialization doesn't just stop here; it also covers unsupervised learning and essential Silicon Valley best practices for AI innovation. By the program's completion, you’ll be well-equipped to tackle complex real-world problems with machine learning techniques, paving the way for a flourishing career in AI.

This updated and expanded 3-course Specialization not only reflects Andrew Ng's substantial contributions to the AI field through his work at Stanford University, Google Brain, Baidu, and Landing.AI but also leverages his highly-acclaimed original Machine Learning course, which has educated over 4.8 million learners since 2012. Rated 4.9 out of 5, it's your doorway to mastering multiple linear regression, logistic regression, neural networks, decision trees, clustering, dimensionality reduction, and more.

Whether you're aiming to break into AI or advance your machine learning career, starting with the Machine Learning Specialization on Coursera is your step towards success. Join learners worldwide in this engaging program under the categories of Python Courses, Supervised Learning Courses, scikit-learn Courses, NumPy Courses, Linear Regression Courses, and more, all designed to provide you with a broad introduction to modern machine learning techniques.