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Why Memory Training need நினைவாற்றல் பயிற்சி ஏன் தேவையாகிறது?"
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How to Fetch Emails from Outlook Using Python: Step-by-Step Guide
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<!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <meta name="description" content="Learn how to fetch all emails from Outlook using Python with detailed examples for both Outlook Desktop and Office 365."> <meta name="keywords" content="Python, Outlook Emails, Fetch Emails, Microsoft Graph API, pywin32, Office 365"> <meta name="author" content="Your Name"> <title>Fetch Outlook Emails using Python</title> <style> body { font-family: Arial, sans-serif; line-height: 1.6; margin: 0; padding: 0; background: #f4f4f4...
Python + Excel: The Ultimate Combination for Data-Driven Decision Making
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Supercharging Excel with Python: A Guide to Boosting Productivity and Analysis Supercharging Excel with Python: A Guide to Boosting Productivity and Analysis - Raghu Vasanth Microsoft Excel has been a go-to tool for data organization, analysis, and visualization for years. However, as data analysis becomes more complex, Excel alone may not always be enough to perform advanced tasks efficiently. That’s where Python, a versatile programming language, comes in. By combining Excel’s familiar interface with Python’s powerful data manipulation and analysis capabilities, you can greatly expand Excel’s functionality for automation, data processing, and even machine learning. In this blog, we’ll explore various ways to use Python in Excel, from basic integrations to more advanced applications. Whether you’re a data analyst, accountant, or Excel enthusiast, learning to use Python with Excel will help streamline your workflow and add versatility to your projects. Why Use...
From Dimensions to Formulas: How Machine Learning help Reverse Engineering
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Automating Formula Discovery: Using Machine Learning to Uncover Dimensional Relationships in Product Design Automating Formula Discovery: Using Machine Learning to Uncover Dimensional Relationships in Product Design -Raghu Vasanth In industries with extensive product catalogs, especially those involving standardized parts with slight variations (e.g., furniture components, building materials, or machinery parts), accurately deriving or predicting key product parameters based on dimensional inputs can save time and resources. Traditionally, engineers and designers use predefined formulas for such calculations. However, with thousands of similar products, each with slightly different dimensions, manual formula creation can become impractical. Here’s where machine learning (ML) steps in as a powerful tool to automatically identify relationships between dimensions and desired parameters, revealing insights and even formulas that are otherwise hard to detect. This blog co...