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

KDnuggets

In this article, Ill walk you through creating a pipeline that processes e-commerce transactions. Well grab data from a CSV file (like youd download from an e-commerce platform), clean it up, and store it in a proper database for analysis. Nothing fancy, just practical code that gets the job done.

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Run the Full DeepSeek-R1-0528 Model Locally

KDnuggets

Download and configure the 1.78-bit Ollama is a lightweight server for running large language models locally. Install it on an Ubuntu distribution using the following commands: apt-get update apt-get install pciutils -y curl -fsSL [link] | sh Step 2: Download and Run the Model Run the 1.78-bit

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Automate Data Quality Reports with n8n: From CSV to Professional Analysis

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By subscribing you accept KDnuggets Privacy Policy Leave this field empty if youre human: Get the FREE ebook The Great Big Natural Language Processing Primer and The Complete Collection of Data Science Cheat Sheets along with the leading newsletter on Data Science, Machine Learning, AI & Analytics straight to your inbox.

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10 GitHub Awesome Lists for Data Science

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After Kaggle, this is one of the best sources for free datasets to download and enhance your data science portfolio. It is ideal for data science projects, machine learning experiments, and anyone who wants to work with real-world data. By subscribing you accept KDnuggets Privacy Policy Leave this field empty if youre human: No, thanks!

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10 Free Online Courses to Master Python in 2025

KDnuggets

Google’s Python Class Platform: Google for Education Level: Intermediate Why Take It: A hands-on course with downloadable lecture notes and exercises created by Google engineers. Computer science foundations: Algorithms, data structures, and how they apply in Python. #

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Deploying the Magistral vLLM Server on Modal

KDnuggets

We will also set environment variables to optimize model downloads and inference performance. To avoid repeated downloads and speed up cold starts, create two Modal Volumes. 🎉 View Deployment: [link] After deployment, the server will begin downloading the model weights and loading them onto the GPUs. and all required packages.

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Building a Custom PDF Parser with PyPDF and LangChain

KDnuggets

The PDF I’m using is publicly accessible, and you can download it using the link. Show extracted image metadata") choice = input("Enter the number of your choice: ").strip() strip() if choice not in {1, 2, 3, 4, 5, 6, 7, 8}: print("❌ Invalid option.") return file_path = input("Enter the path to your PDF file: ").strip() page_content[:500], ".")