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Data Science Tutorials

Develop your data science skills with tutorials in our blog. We cover everything from intricate data visualizations in Tableau to version control features in Git.
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Excel ROUNDUP(): When You Want More, Not Less

Discover how to use the ROUNDUP() function in Excel to consistently round numbers away from zero. Learn the syntax, see examples, and compare ROUNDUP() with other rounding methods.
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Allan Ouko

12 giugno 2025

Magistral Small: A Guide With Demo Project on vLLM and Ollama

Learn how to set up and run Mistral's Magistral Small model using Ollama and vLLM, and build a demo project that debugs faulty logic.
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Aashi Dutt

12 giugno 2025

The T-Distribution: A Key Tool for Small Sample Inference

Understand how the t-distribution helps when sample sizes are small or population variance is unknown. Compare it to the normal and Z-distributions to learn when each is appropriate.
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Vidhi Chugh

11 giugno 2025

PI() in Excel: How to Use and Apply π in Your Formulas

Learn how to use PI() in Excel so you have precision with mathematical formulas. Discover examples, syntax details, and tips for harnessing π in calculations.
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Josef Waples

11 giugno 2025

Excel SEQUENCE(): A Helpful Guide to Dynamic Arrays

Master the `SEQUENCE()` function to supercharge your spreadsheet skills. Learn how to create dynamic lists, automate calculations, and unlock new Excel possibilities.
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Josef Waples

10 giugno 2025

Azure Cosmos DB: A Global-Scale NoSQL Cloud Database

Discover how Microsoft’s fully managed, multi-model database delivers low-latency performance, elastic scalability, and real-time capabilities for AI, IoT, e-commerce, and more.
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Josep Ferrer

9 giugno 2025

Amazon Neptune: A Look into AWS’s Fully Managed Graph Database

Understand how Amazon Neptune handles highly connected data using graph models like property graphs and RDF. Discover how to write queries in Gremlin, openCypher, and SPARQL for real-world tasks like fraud detection and recommendations.
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Iheb Gafsi

9 giugno 2025

PySpark Filter Tutorial: Techniques, Performance Tips, and Use Cases

Learn efficient PySpark filtering techniques with examples. Boost performance using predicate pushdown, partition pruning, and advanced filter functions.
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Derrick Mwiti

8 giugno 2025

PySpark Read CSV: Efficiently Load and Process Large Files

Learn how to read CSV files efficiently in PySpark. Explore options, schema handling, compression, partitioning, and best practices for big data success.
Derrick Mwiti's photo

Derrick Mwiti

8 giugno 2025