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Difference Between == and is Operator in Python

Analytics Vidhya

Introduction In Python, the == and is operators are often used for comparison by programmers. Although they might seem similar at first glance, they are understood to operate differently, and their differences are considered important for anyone coding in Python to grasp.

Python 292
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Mastering the Division Operator in Python

Analytics Vidhya

Introduction The division operator is a cornerstone in Python programming, facilitating mathematical computations and maneuvers. This extensive manual ventures into the depths of the division operator in Python, encompassing its diverse manifestations and utilities.

Python 252
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Python Membership and Identity Operators: Understanding the Basics

Analytics Vidhya

Introduction Unlocking the potential for intuitive and expressive code, operator overloading in Python stands as a cornerstone of flexibility and customizability. It empowers developers to infuse their classes with operator semantics, bridging the gap between abstract concepts and concrete implementations.

Python 275
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Here’s All About the Operator Overloading in Python

Analytics Vidhya

Introduction Unlocking the potential for intuitive and expressive code, operator overloading in Python stands as a cornerstone of flexibility and customizability. It empowers developers to infuse their classes with operator semantics, bridging the gap between abstract concepts and concrete implementations.

Python 261
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The Key to Sustainable Energy Optimization: A Data-Driven Approach for Manufacturing

Speaker: Kevin Kai Wong, President of Emergent Energy Solutions

📊 Join us for a practical webinar hosted by Kevin Kai Wong of Emergent Energy, where we'll explore how leveraging data-rich energy management solutions can drive operational excellence in the evolving landscape of energy intelligence and sustainability in manufacturing! 🌎 Don't miss this valuable webinar opportunity!

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6 Major Bitwise Operators in Python

Analytics Vidhya

Introduction Bitwise operators are essential to Python programming, allowing you to manipulate individual bits of an integer. Understanding how to use these operators can significantly enhance your programming skills and open up new possibilities for solving complex problems.

Python 268
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Python Modulo Operator: Common Errors and How to Use

Analytics Vidhya

The modulo operator (%) holds a special place among its myriad built-in operators, offering a convenient means to calculate remainders and perform cyclic operations. Introduction Python stands out for its simplicity, versatility, and power in the realm of programming languages.

Python 301
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New Study: 2018 State of Embedded Analytics Report

Why do some embedded analytics projects succeed while others fail? We surveyed 500+ application teams embedding analytics to find out which analytics features actually move the needle. Read the 6th annual State of Embedded Analytics Report to discover new best practices. Brought to you by Logi Analytics.

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How to Package and Price Embedded Analytics

Just by embedding analytics, application owners can charge 24% more for their product. How much value could you add? This framework explains how application enhancements can extend your product offerings. Brought to you by Logi Analytics.

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6 Best Practices for Operational Reporting

In our eBook, you’ll learn the do’s and don’ts to embedding operational reports, and how to avoid common reporting mistakes. Meeting requirements alone is no longer enough. Today’s users need insightful reporting built on accurate, real-time data.

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How to Build an Experimentation Culture for Data-Driven Product Development

Speaker: Margaret-Ann Seger, Head of Product, Statsig

In this webinar, Margaret-Ann Seger, Head of Product at Statsig, will teach you how to build an experimentation culture from the ground-up, graduating from just getting started with data-driven development to operating at the level of a FAANG company!

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LLMs in Production: Tooling, Process, and Team Structure

Speaker: Dr. Greg Loughnane and Chris Alexiuk

However, during development – and even more so once deployed to production – best practices for operating and improving generative AI applications are less understood.