With the subtitle "Using Data Science to Transform Information into Insight", this book is a field guide to building statistics, machine learning, and powerful artificial intelligence concepts inside the spreadsheet. In this updated edition, author Jordan Goldmeier shows how to implement data science problems using Excel while exposing how things work behind the scenes.
Author: Jordan Goldmeier Publisher: Wiley Date: November 2023 Pages: 448 ISBN: 978-1119931386 Print: 111993138X Kindle: B0CJPP7XZM Audience: Excel users Level: Introductory Category: Data Science
Topics include:
- Cutting-edge Excel tools Power Query and new functions like XLOOKUP, LET and LAMBDA
- Creating artificial intelligence using linear models, ensemble methods, and naïve Bayes
- Mathematical optimization, including non-linear programming and genetic algorithms
- Prediction with time-series data and forecasting with exponential smoothing
- Clustering with k-means, spherical k-means, and graph modularity
- Quantifying and addressing risk with Monte Carlo simulation
- Detecting outliers in single or multiple dimensions
- Statistical programming with R
For recommendations of books on data science see Reading Your Way Into Big Data in our Programmer's Bookshelf section.
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Algorithms: Absolute Beginner's Guide
Author: Kirupa Chinnathambi Publisher: Addison-Wesley Date: November 2023 Pages: 416 ISBN: 978-0138222291 Print: 0138222290 Kindle: B0CCTZ37DQ Audience: General Rating: 4.5 Reviewer: Kay Ewbank
Subtitled 'a practical introduction to data structures and algorithms in JavaScript', this book is split into tw [ ... ]
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Quick Start Guide to Large Language Models
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