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From Extraction to Accuracy: Evaluating Extracted Invoice Data with LLM-as-a-Judge
Last Updated on March 11, 2026 by Editorial Team Author(s): Krishnan Srinivasan Originally published on Towards AI. (A practical, end-to-end guide to building a ground-truth-based evaluation pipeline, complete with synthetic data and runnable SQL on Snowflake) In the earlier parts of this Agentic AI series, we explored how AI systems can reason, use tools, retrieve knowledge, an...

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Nobody Invented Attention. A Frustrated PhD Student Ran Out of Other Options.
Last Updated on March 11, 2026 by Editorial Team Author(s): DrSwarnenduAI Originally published on Towards AI. Nobody Invented Attention. A Frustrated PhD Student Ran Out of Other Options. Dzmitry Bahdanau was not trying to invent the architecture that would eventually run inside every large language model on earth. Completely gibberish at this stage!!!!wait!!!!!! Be with me!!!!!...

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Part 9: Data Manipulation in Data Merging and Joins
Last Updated on March 11, 2026 by Editorial Team Author(s): Raj kumar Originally published on Towards AI. Every analysis that combines data from multiple sources faces the same fundamental question: how should these datasets align? Which records match? What happens when they don’t? These aren’t just technical decisions. They shape what your analysis says and what it hides. Data ...

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Part 8: Data Manipulation in Grouping and Aggregation
Last Updated on March 11, 2026 by Editorial Team Author(s): Raj kumar Originally published on Towards AI. Every business decision starts with a question. What are our total sales by region? Which product categories generate the most revenue? How do customer segments compare in profitability? These questions all share something in common: they require grouping data and calculatin...

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Part 7: Data Manipulation in Date and Time Handling
Last Updated on March 11, 2026 by Editorial Team Author(s): Raj kumar Originally published on Towards AI. Time is the invisible thread that runs through almost every dataset you’ll encounter. Sales happen on specific dates. Transactions occur at precise moments. Events unfold across hours, days, and years. Yet despite how fundamental time is to data analysis, working with dates ...

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