Hands-On Machine Learning with Microsoft Excel 2019

3.6 (5 reviews total)
By Julio Cesar Rodriguez Martino
    Advance your knowledge in tech with a Packt subscription

  • Instant online access to over 7,500+ books and videos
  • Constantly updated with 100+ new titles each month
  • Breadth and depth in over 1,000+ technologies
  1. Section 1: Machine Learning Basics

About this book

We have made huge progress in teaching computers to perform difficult tasks, especially those that are repetitive and time-consuming for humans. Excel users, of all levels, can feel left behind by this innovation wave. The truth is that a large amount of the work needed to develop and use a machine learning model can be done in Excel.

The book starts by giving a general introduction to machine learning, making every concept clear and understandable. Then, it shows every step of a machine learning project, from data collection, reading from different data sources, developing models, and visualizing the results using Excel features and offerings. In every chapter, there are several examples and hands-on exercises that will show the reader how to combine Excel functions, add-ins, and connections to databases and to cloud services to reach the desired goal: building a full data analysis flow. Different machine learning models are shown, tailored to the type of data to be analyzed.

At the end of the book, the reader is presented with some advanced use cases using Automated Machine Learning, and artificial neural network, which simplifies the analysis task and represents the future of machine learning.

Publication date:
April 2019


Section 1: Machine Learning Basics

The objective of part 1 is to introduce the reader to machine learning and the different types of models used. It will cover supervised and unsupervised learning, the principal division within machine learning. Within these aspects, the difference between regression (continuous target variable) and classification (discrete target variable) will be demonstrated. All points are explained by means of hands-on examples.

This section comprises the following chapters:

  • Chapter 1, Implementing Machine Learning Algorithms
  • Chapter 2, Hands-On Examples of Machine Learning Models

About the Author

  • Julio Cesar Rodriguez Martino

    Julio Cesar Rodriguez Martino is a machine learning (ML) and artificial intelligence (AI) platform architect, focusing on applying the latest techniques and models in these fields to optimize, automate, and improve the work of tax and accounting consultants. The main tool used in this practice is the MS Office platform, which Azure services complement perfectly by adding intelligence to the different tasks.

    Julio's background is in experimental physics, where he learned and applied advanced statistical and data analysis methods. He also teaches university courses and provides in-company training on machine learning and analytics, and has a lot of experience leading data science teams.

    Browse publications by this author

Latest Reviews

(5 reviews total)
BS book - it was about excel math functions and not Machine learning
Le livre est intéressant, les formations sont pertinentes, merci à packt.
Livro excelente, instrutivo e com exemplos.

Recommended For You

Book Title
Unlock this book and the full library for FREE
Start free trial