Book Image

Hands-on Machine Learning for Data Mining [Video]

By : Jesus Salcedo
Book Image

Hands-on Machine Learning for Data Mining [Video]

By: Jesus Salcedo

Overview of this book

<p>30% of data mining vacancies also involve machine learning. And those that do are 30% better paid than the rest. If you’re involved in data mining you need to get on top of machine learning, before it gets on top of you.</p> <p>Hands-On Machine Learning for Data Mining gives you everything you need to bring the power of machine learning into your data mining work. This video course will enable you to pair the best algorithms with the right tools and processes. You will see how systems can learn from data, identify patterns and make predictions on data with minimal human intervention.</p> <p>All the code and supporting files for this course are available on Github at&nbsp;<a href="https://github.com/PacktPublishing/Hands-on-Machine-Learning-for-Data-Mining-V-" target="_blank">https://github.com/PacktPublishing/Hands-on-Machine-Learning-for-Data-Mining-V-</a></p> <h1>Style and Approach</h1> <p>This is an application-oriented course and the approach will be practical. This course will discuss the situations in which you would use each data mining technique, the assumptions made by the method, how to set up the analysis and how to interpret the results. No proofs will be derived, but rather the focus will be on the practical matters of data analysis in support of improving predictive models.</p>
Table of Contents (4 chapters)
Chapter 3
Improving Individual Models
Content Locked
Section 3
Removing Noise
This video discusses how to remove noise from models. - Removing irrelevant predictors - Consequences of having irrelevant predictors