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 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 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.

71 pages, Kindle Edition

Published November 7, 2018

Reviews

[Mazzeo Mattola · Rating 1 out of 5]

Not enough explanation, not enough information to justify a book instead of a single Facebook post. Also, its just a render of some noteboos. Dropshipping materials.