Logistic Regression with NumPy and Python
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.
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- Level Beginner
- Duration 2 hours
- Course by Coursera Project Network
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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.Modules
Logistic Regression with NumPy and Python
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- Graded Quiz: Test Your Project Understanding
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- Logistic Regression with NumPy and Python
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- Project-Based Course Overview
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Dive into "Logistic Regression with NumPy and Python," a hands-on data science course by Coursera. Guided by expert instructors, you'll build logistic regression models from scratch using Python and NumPy, without relying on libraries like scikit-learn. Ideal for beginners with basic Python and machine learning knowledge, this 120-minute course offers free access to a cloud desktop with all necessary software. Perfect for those looking to deepen their understanding of machine learning fundamentals through practical, project-based learning.
Snehan Kekre