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Excel For Data Analysis & Machine Learning (Bisette, Vincent, Van Der Post, Hayden, Preston, James) - Nyomtatható verzió

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RE: Excel For Data Analysis & Machine Learning (Bisette, Vincent, Van Der Post, Hayden, Preston, James) - Farid-Khan - 2025-11-20

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English | 2025 | ISBN: 9798266298477 | 663 pages | True EPUB | 0.63 MB 0470132299

Catergory: Computer Technology, Nonfiction

Idézet:Excel for Data Analysis & Machine Learning: Transform, Visualize, and Automate Insights: Power Query, PivotTables, and Python Integration for Advanced ... and Automation
Reactive Publishing
Excel isn't just for spreadsheets anymore, it's one of the most powerful data analysis and automation platforms available. Excel for Data Analysis & Machine Learning teaches you how to turn raw data into actionable insights, build interactive dashboards, and even integrate Python workflows for next-level analytics.
This book takes you beyond basic formulas, showing you how to use Excel as a data transformation engine, analytics platform, and lightweight machine learning tool.
Inside, you'll master
Power Query for ETL Pipelines - Automate data cleaning, merging, and reshaping from multiple sources.
PivotTables & Dashboards - Create interactive visualizations with slicers, timelines, and dynamic charts.
Built-In Analysis Tools - Use Solver, Analysis ToolPak, and regression tools to build predictive models.
Excel for Machine Learning - Implement clustering, classification, and forecasting workflows step-by-step.
Python Integration - Supercharge Excel with Python scripts using xlwings and pandas for automation.
Data Storytelling & Presentation - Deliver insights that decision-makers can act on.
Whether you're a data analyst, business professional, or student, this book will help you transform Excel from a simple spreadsheet tool into a powerful data science companion.

Contents of Download:
Idézet:? Excel For Data Analysis.epub (Bisette, Vincent, Van Der Post, Hayden, Preston, James) (2025) (631.59 KB)

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⭐️ Excel For Data Analysis & Machine Learning ✅ (1.7 MB)
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