Scikit-Learn to Solve Regression Machine Learning Problems
Hello everyone and welcome to this new hands-on project on Scikit-Learn for solving machine learning regression problems. In this project, we will learn how to build and train regression models using Scikit-Learn library. Scikit-learn is a free machine learning library developed for python. Scikit-learn offers several algorithms for classification, regression, and clustering. Several famous machine learning models are included such as support vector machines, random forests, gradient boosting, and k-means. This project is practical and directly applicable to many industries.
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- Level Beginner
- Duration 3 hours
- Course by Coursera Project Network
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About
Hello everyone and welcome to this new hands-on project on Scikit-Learn for solving machine learning regression problems. In this project, we will learn how to build and train regression models using Scikit-Learn library. Scikit-learn is a free machine learning library developed for python. Scikit-learn offers several algorithms for classification, regression, and clustering. Several famous machine learning models are included such as support vector machines, random forests, gradient boosting, and k-means. This project is practical and directly applicable to many industries. You can add this project to your portfolio of projects which is essential for your next job interview.Modules
Your Learning Journey
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- Assess Your Knowledge
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- Scikit-Learn to Solve Regression ML Problems
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- Project Overview
Auto Summary
Dive into the world of data science with "Scikit-Learn to Solve Regression Machine Learning Problems." This beginner-level course, taught on Coursera, focuses on building and training regression models using the Scikit-Learn library. Spanning 180 minutes, it offers practical, industry-relevant skills ideal for enhancing your project portfolio. Accessible for free, it's perfect for aspiring data scientists and AI enthusiasts.
Ryan Ahmed