Getting Started with Scikit-Learn: A Beginner’s Guide to ML

Foundations and Practical Applications

Created by: Jitendra Singh
Edtech company

What Will I Learn?

• Fundamental concepts of Machine Learning and its various types.
• Hands-on knowledge of various Machine Learning algorithms using the Scikit-Learn library.
• Techniques to pre-process data, select the right model, train, test, and evaluate Machine Learning models.
• Practical understanding of how to use Scikit-Learn for regression, classification, clustering, and dimensionality reduction tasks.
• Model evaluation techniques and the understanding of underfitting and overfitting.

Requirements

• Basic knowledge of Python programming is required as the course will be taught using Python.
• Familiarity with basic mathematical concepts would be beneficial but not mandatory.
• A computer with an Internet connection to download necessary libraries and datasets.
• No prior knowledge of Machine Learning or Scikit-Learn is required.

Target audience

• Beginners who are interested in Machine Learning and want to understand it through practical applications.
• Python programmers who are interested in Machine Learning and want to learn how to implement Machine Learning algorithms using Scikit-Learn.
• Data analysts or data scientists who want to upgrade their skills by learning Machine Learning techniques.
• Anyone who is curious about how Machine Learning models work and how they can be implemented using Scikit-Learn.