Logistic Regression with NumPy and Python
$9.99
ENROLL NOWCourse Overview
What You'll Learn
- In this project, you will do all the machine learning without using any of the popular machine learning libraries such as scikit-learn and statsmodels.
- The aim of this project and is to implement all the machinery, including gradient descent, cost function, and logistic regression, of the various learning algorithms yourself, so you have a deeper understanding of the fundamentals.
- By the time you complete this project, you will be able to build a logistic regression model using Python and NumPy, conduct basic exploratory data analysis, and implement gradient descent from scratch.
Welcome to this project-based course on Logistic with NumPy and Python. In this project, you will do all the machine learning without using any of the popular machine learning libraries such as scikit-learn and statsmodels. The aim of this project and is to implement all the machinery, including gradient descent, cost function, and logistic regression, of the various learning algorithms yourself, so you have a deeper understanding of the fundamentals. By the time you complete this project, you will be able to build a logistic regression model using Python and NumPy, conduct basic exploratory data analysis, and implement gradient descent from scratch. The prerequisites for this project are prior programming experience in Python and a basic understanding of machine learning theory. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, NumPy, and Seaborn pre-installed.
Course FAQs
Is this an accredited online course?
Accreditation for 'Logistic Regression with NumPy and Python' is determined by the provider, Coursera Project Network. For online college courses or degree programs, we strongly recommend you verify the accreditation status directly on the provider's website to ensure it meets your requirements.
Can this course be used for continuing education credits?
Many of the courses listed on our platform are suitable for professional continuing education. However, acceptance for credit varies by state and licensing board. Please confirm with your board and {course.provider} that this specific course qualifies.
How do I enroll in this online school program?
To enroll, click the 'ENROLL NOW' button on this page. You will be taken to the official page for 'Logistic Regression with NumPy and Python' on the Coursera Project Network online class platform, where you can complete your registration.
