This book is a guide for you on how to use Scikit-Learn, a machine learning library for Python programming language. The author first helps you know what Scikit-Learn are and how to set it up on your system. You are also guided on how to load datasets into Scikit-Learn. The author has then guided you on how to use the various machine learning algorithms to implement machine learning models of different types with Scikit-Learn. Some of the algorithms that have been discussed include Support Vector Machine (SVM), Linear Regression, K-Nearest Neighbors and K-Means. In all these, practical examples have been given, hence you will know how to implement models and use them for making predictions.
The content is:
- Getting Started with Scikit-learn
- Support Vector Machines in Scikit-learn
- Scikit-Learn Linear Regression
- Scikit-Learn k-Nearest Neighbors Classifier
- K-Means Clustering With Scikit-Learn
Subjects include: python programming language, python, linear regression book, scikit-learn, scikit-learn and tensorflow, support vector machine, linear regression, k-nearest neighbor, k-means, kernel, linear regression models, data visualisation, linear regression analysis, linear regression machine learning.
