Free Certification Course Title: 2023 Python for Linear Regression in Machine Learning
Linear & Non-Linear Regression, Lasso & Ridge Regression, SHAP, LIME, Yellowbrick, Feature Selection & Outliers Removal
2023 Python for Linear Regression in Machine Learning [FREE]
Description:
Unlock the power of machine learning with our comprehensive Python course on linear regression. Learn how to use Python to analyze data and build predictive models. This course is perfect for beginners with little or no programming experience and experienced Python developers looking to expand their skill set.
You’ll start with the basics of Python and work your way up to advanced techniques like linear regression, which is a powerful tool for predicting future outcomes based on historical data. Along the way, you’ll gain hands-on experience with popular Python libraries such as NumPy, Pandas, and Matplotlib. We will also cover the important aspect of model optimization, interpretability, and feature selection. You will learn how to optimize your model to improve its performance and how to interpret the model results and understand the underlying relationships in your data. We will also discuss feature selection techniques that are used to identify the most essential features that drive the predictions.
By the end of the course, you’ll have a solid understanding of how to use Python to build linear regression models and make accurate predictions. You’ll also be able to apply your new skills to a wide range of machine learning and data science projects. So, if you’re ready to take your Python skills to the next level and start using machine learning to analyze and predict real-world outcomes, this is the course for you!
What you’ll learn:
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Analyse and visualize data using Linear Regression
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Plot the graph of results of Linear Regression to visually analyze the results
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Learn how to interpret and explain machine learning models
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Do in-depth analysis of various forms of Linear and Non-Linear Regression
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Use YellowBrick, SHAP, and LIME to interact with predictions of machine learning models
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Do feature selection and transformations to fine tune machine learning models
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Course contains result oriented algorithms and data explorations techniques
