Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Hands-On Machine Learning with Microsoft Excel 2019

You're reading from   Hands-On Machine Learning with Microsoft Excel 2019 Build complete data analysis flows, from data collection to visualization

Arrow left icon
Product type Paperback
Published in Apr 2019
Publisher Packt
ISBN-13 9781789345377
Length 254 pages
Edition 1st Edition
Tools
Arrow right icon
Author (1):
Arrow left icon
Julio Cesar Rodriguez Martino Julio Cesar Rodriguez Martino
Author Profile Icon Julio Cesar Rodriguez Martino
Julio Cesar Rodriguez Martino
Arrow right icon
View More author details
Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: Machine Learning Basics FREE CHAPTER
2. Implementing Machine Learning Algorithms 3. Hands-On Examples of Machine Learning Models 4. Section 2: Data Collection and Preparation
5. Importing Data into Excel from Different Data Sources 6. Data Cleansing and Preliminary Data Analysis 7. Correlations and the Importance of Variables 8. Section 3: Analytics and Machine Learning Models
9. Data Mining Models in Excel Hands-On Examples 10. Implementing Time Series 11. Section 4: Data Visualization and Advanced Machine Learning
12. Visualizing Data in Diagrams, Histograms, and Maps 13. Artificial Neural Networks 14. Azure and Excel - Machine Learning in the Cloud 15. The Future of Machine Learning 16. Assessment

Who this book is for

This book is aimed at data analysts using Excel as their everyday tool, who need to go beyond Power Pivot and use add-ins and other advanced tools. Excel experts wanting to expand their knowledge to take advantage of the new connection possibilities between Excel and Azure will also benefit, as will project managers needing to test machine learning models without writing code.

It is generally taken for granted that, in order to do data science, from data cleansing to visualization and machine learning models, you need to be a Python or R programmer. This is not the case nowadays, and the general tendency seems to be heading toward code-free data science. The reader needs to learn that there are other options, avoiding code to take Excel to the next level and use it as a platform for professional data analysis and visualization.

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image