Introduction to Machine Learning and Scikit Learn Library

Machine learning is a branch of artificial intelligence that focuses on the development of algorithms and models that allow computers to learn and make decisions based on data. It is a powerful tool that is used in various industries such as finance, healthcare, marketing, and more.

What is Scikit Learn Library?

Scikit Learn is a popular machine learning library in Python that provides simple and efficient tools for data mining and data analysis. It is built on top of NumPy, SciPy, and matplotlib, making it easy to use and integrate with other scientific computing libraries.

Why use Scikit Learn?

Scikit Learn is widely used in the machine learning community for several reasons:

• It has a simple and consistent API that makes it easy to use and understand.
• It provides a wide range of machine learning algorithms such as classification, regression, clustering, and dimensionality reduction.
• It includes tools for model selection, evaluation, and tuning.
• It is open source and well-documented, with a large community of users and contributors.

Getting Started with Scikit Learn

To get started with Scikit Learn, you first need to install the library. You can do this using pip, the Python package manager, by running the following command:

pip install scikit-learn

Once you have installed Scikit Learn, you can start using its functionality to build machine learning models. In the next part of this series, we will explore some common machine learning algorithms and how to implement them using Scikit Learn.