Supervised Machine Learning - Regression and Classification Coursera

Overview

In the Supervised Machine Learning - Regression and Classification course offered by Coursera in partnership with Stanford you will:

• Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn.

• Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression

Key facts

In the first course of the Machine Learning Specialization, you will:

• Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn.

• Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression

What you will learn

• The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. In this beginner-friendly program, you will learn the fundamentals of machine learning and how to use these techniques to build real-world AI applications. 

• This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field.

• This 3-course Specialization is an updated and expanded version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012. 

Skills you'll gain

• Applied Machine Learning

• Supervised Learning

• Data-Driven Decision-Making

• Classification And Regression Tree (CART)

• NumPy

• Regression Analysis

• Predictive Modeling

• Algorithms