Scikit-learn in Details: Deep understanding

By Robert Collins

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-LearnSubjects 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.

• Format: Paperback
• Language: English
• ISBN: 1731040512
• ISBN13: 9781731040510
• Release Date: November 2018
• Publisher: Independently Published
• Length: 70 Pages
• Weight: 0.23 lbs.
• Dimensions: 0.1" x 6.0" x 9.0"