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10 Surprising Things You Can Do with Python’s collections Module

KDnuggets

This makes your code more readable than using a standard tuple. This makes your code more readable than using a standard tuple. This makes your code more readable than using a standard tuple. They definitely have their uses.

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Building End-to-End Data Pipelines: From Data Ingestion to Analysis

KDnuggets

By Josep Ferrer , KDnuggets AI Content Specialist on July 15, 2025 in Data Science Image by Author Delivering the right data at the right time is a primary need for any organization in the data-driven society. Image by Author It is a common misconception to equate a data pipeline with any form of data movement.

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Build a Data Cleaning & Validation Pipeline in Under 50 Lines of Python

KDnuggets

By Bala Priya C , KDnuggets Contributing Editor & Technical Content Specialist on June 24, 2025 in Python Image by Author | Ideogram Data is messy. Currently, shes working on learning and sharing her knowledge with the developer community by authoring tutorials, how-to guides, opinion pieces, and more.

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Build ETL Pipelines for Data Science Workflows in About 30 Lines of Python

KDnuggets

By Bala Priya C , KDnuggets Contributing Editor & Technical Content Specialist on July 8, 2025 in Data Science Image by Author | Ideogram You know that feeling when you have data scattered across different formats and sources, and you need to make sense of it all? Start here with a simple Python pipeline that covers the essentials.

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Apache Airflow® Crash Course: From 0 to Running your Pipeline in the Cloud

With over 30 million monthly downloads, Apache Airflow is the tool of choice for programmatically authoring, scheduling, and monitoring data pipelines. Airflow enables you to define workflows as Python code, allowing for dynamic and scalable pipelines suitable to any use case from ETL/ELT to running ML/AI operations in production.

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10 Python Math & Statistical Analysis One-Liners

KDnuggets

By Bala Priya C , KDnuggets Contributing Editor & Technical Content Specialist on July 16, 2025 in Python Image by Author | Ideogram Pythons expressive syntax along with its built-in modules and external libraries make it possible to perform complex mathematical and statistical operations with remarkably concise code.

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Serve Machine Learning Models via REST APIs in Under 10 Minutes

KDnuggets

By Kanwal Mehreen , KDnuggets Technical Editor & Content Specialist on July 4, 2025 in Machine Learning Image by Author | Canva If you like building machine learning models and experimenting with new stuff, that’s really cool — but to be honest, it only becomes useful to others once you make it available to them.

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Monetizing Analytics Features: Why Data Visualizations Will Never Be Enough

Think your customers will pay more for data visualizations in your application? Five years ago they may have. But today, dashboards and visualizations have become table stakes. Discover which features will differentiate your application and maximize the ROI of your embedded analytics. Brought to you by Logi Analytics.

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How to Find and Test Assumptions in Product Development

Watch this webinar with Laura Klein, product manager and author of Build Better Products, to learn how to spot the unconscious assumptions which you’re basing decisions on and guidelines for validating (or invalidating) your ideas. Assumptions mapping is the process of identifying and testing your riskiest ideas.

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Let's Get Physical: How to Blend Direct Mail Marketing with Your Digital Strategy

Speaker: Akeel Jabber, B2B SaaS Investor and Growth Marketer at Horizen Capital

This exclusive webinar with industry authorities Akeel Jabber and Bruce McMeekin will explore the dynamic duo of direct mail marketing and digital marketing, and teach you how to get started with blending these approaches into an effective and impactful marketing strategy! where should you start?

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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.