Coursera
Coursera Logo

Supervised Machine Learning: Regression and Classification 

  • Offered byCoursera

Supervised Machine Learning: Regression and Classification
 at 
Coursera 
Overview

Gain a comprehensive overview of the Machine Learning principles and concepts

Duration

33 hours

Start from

Start Now

Total fee

Free

Mode of learning

Online

Difficulty level

Beginner

Official Website

Explore Free Course External Link Icon

Credential

Certificate

Supervised Machine Learning: Regression and Classification
 at 
Coursera 
Highlights

  • Earn a certificate of completion
Details Icon

Supervised Machine Learning: Regression and Classification
 at 
Coursera 
Course details

Skills you will learn
More about this course
  • 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
  • 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

Supervised Machine Learning: Regression and Classification
 at 
Coursera 
Curriculum

Week 1: Introduction to Machine Learning

Welcome to machine learning!

Applications of machine learning

What is machine learning?

Supervised learning part

Supervised learning part

Unsupervised learning part

Unsupervised learning part

Jupyter Notebooks

Linear regression model part

Linear regression model part

Cost function formula

Cost function intuition

Visualizing the cost function

Week 2: Regression with multiple input variables

Multiple features

Vectorization part

Vectorization part

Gradient descent for multiple linear regression

Feature scaling part

Feature scaling part

Checking gradient descent for convergence

Choosing the learning rate

Feature engineering

Polynomial regression

Week 3: Classification

Motivations

Logistic regression

Decision boundary

Cost function for logistic regression

Simplified Cost Function for Logistic Regression

Gradient Descent Implementation

The problem of overfitting

Addressing overfitting

Cost function with regularization

Supervised Machine Learning: Regression and Classification
 at 
Coursera 
Admission Process

    Important Dates

    May 25, 2024
    Course Commencement Date

    Other courses offered by Coursera

    – / –
    3 months
    Beginner
    – / –
    20 hours
    Beginner
    – / –
    2 months
    Beginner
    – / –
    3 months
    Beginner
    View Other 6715 CoursesRight Arrow Icon
    qna

    Supervised Machine Learning: Regression and Classification
     at 
    Coursera 

    Student Forum

    chatAnything you would want to ask experts?
    Write here...