Faster dataframe engines are nice, but they don't reduce the amount of syntax an analyst has to hold in their head. The post The Problem with pandas Isn’t Performance.
How Gemini solved my Pandas problem in seconds, and why data science fundamentals still matter to spot suboptimal solutions The post I Spent an Hour on a Data Preprocessing Task Before Asking Gemini appeared first on Towards Data Science .
Not all Python data libraries are created equal! The post Should AI Developers Make the Switch from Polars to Pandas?
Enterprise Document Intelligence [Vol. 1 #7A] - Stop searching strings.
How Pandas chunking, Dask, and Polars help process millions of records when adding more compute isn't an option. The post What Can We Do When Memory Becomes the New Bottleneck in Data Engineering?
The true bottleneck was never the analysis. The post BI Is Dead, Long Live BI appeared first on Towards Data Science .
Two techniques, two different problems, and why the question is not really "which one wins" The post RAG vs Fine-Tuning Explained: What They Actually Do and When to Use Each appeared first on Towards Data Science .
Exploring GPU acceleration with cuDF, cudf. pandas, and the Polars GPU Engine The post How Much of a Data Science Workflow Can Run on a GPU Today?
Maximize your efficiency with Claude Code The post How to Efficiently Prompt Claude Code appeared first on Towards Data Science .
The barriers to building have collapsed. That shifts the bottleneck to ownership, validation, taste, and deciding what should actually exist The post Code Is Cheap.
Enterprise Document Intelligence [Vol. 1 #5B] - One PDF in, a relational set of DataFrames out: lines, pages, TOC, images, cross-references, captions, spans, and a parsing summary The post Stop Returning Flat Text from a PDF: The Relational Tables RAG Needs appeared first on Towards Data Science .
Balancing context capability against cost, speed, and data The post Long Context vs. Short Context Model: When Does a Long Context Model Win?
Enterprise Document Intelligence [Vol. 1 #5B] - One PDF in, a relational set of DataFrames out: lines, pages, TOC, images, cross-references, captions, spans, and a parsing summary The post Stop Returning Flat Text from a PDF: The Relational Shape RAG Needs appeared first on Towards Data Science .