Polynomial Regression in Python - sklearn

Unlock the potential of polynomial regression with this hands-on tutorial using Python and Scikit-Learn. Ideal for beginners and intermediate learners, this video walks you through the process of building and implementing a polynomial regression model from scratch. You’ll learn how to set up your Python environment, preprocess your data, and use Scikit-Learn to create and train your model. The tutorial covers essential concepts like feature engineering, degree selection, and model evaluation, with practical coding examples to help you apply what you’ve learned to real-world datasets. Whether you're working on predicting trends, fitting nonlinear data, or enhancing your regression analysis skills, this video provides the tools and knowledge you need. By the end of this tutorial, you'll have a solid understanding of polynomial regression and how to leverage Python and Scikit-Learn for advanced predictive modeling. Perfect for data scientists, analysts, and anyone looking to elevate their machine learning projects. Please feel free to download the dataset from this link: https://github.com/rashida048/Machine-Learning-Tutorials-Scikit-Learn/blob/main/insurance.csv The complete notebook is available here: https://github.com/rashida048/Machine-Learning-Tutorials-Scikit-Learn/blob/main/Polynomial_Regression.ipynb As mentioned in the video, here is the link to the simple linear regression explanation: https://youtu.be/lkbQzT3FiYM Please feel free to check out my Data Science blog where you will find a lot of data visualization, exploratory data analysis, statistical analysis, machine learning, natural language processing, and computer vision tutorials and projects: https://regenerativetoday.com/ Twitter page: https://twitter.com/rashida048 Facebook Page: https://regenerativetoday.com/ #polynomialregression #machinelearning #datascience #artificialintelligence #dataAnalytics #python #sklearn #jupyternotebook