Book Image

Making Predictions with Data and Python [Video]

By : Alvaro Fuentes
Book Image

Making Predictions with Data and Python [Video]

By: Alvaro Fuentes

Overview of this book

<p>Python has become one of any data scientist's favorite tools for doing Predictive Analytics. In this hands-on course, you will learn how to build predictive models with Python. </p><p> </p><p>During the course, we will talk about the most important theoretical concepts that are essential when building predictive models for real-world problems. The main tool used in this course is scikit -learn, which is recognized as a great tool: it has a great variety of models, many useful routines, and a consistent interface that makes it easy to use. All the topics are taught using practical examples and throughout the course, we build many models using real-world datasets. </p><p> </p><p>By the end of this course, you will learn the various techniques in making predictions about bankruptcy and identifying spam text messages and then use our knowledge to create a credit card using a linear model for classification along with logistic regression. </p><p></p>
Table of Contents (7 chapters)
Chapter 6
Classification: Concepts and Models
Content Locked
Section 3
Naive Bayes Classifiers
Explain at a very high level where the Naïve Bayes models come from and give some of the general characteristics of these models. Talk about the two types of Naïve Bayes that can be used in scikit-learn. - Explain the general idea upon which these models are built - Mention the two types of Naïve Bayes found in scikit-learn - Talk briefly about the objects used in scikit-learn for training these models