Writing secure code is hard. When you learn a language, a module or a framework, you learn how it supposed to be used. When thinking about security, you need to think about how it can be misused.

Each tool serves different needs, from simplicity to speed and SQL-based analytics workflows. Performance differences matter most, with Polars and DuckDB outperforming Pandas on large datasets. Modern ...

In our earlier article, we demonstrated how to build an AI chatbot with the ChatGPT API and assign a role to personalize it. But what if you want to train the AI on your own data? For example, you may ...

Spreadsheet apps like Microsoft Excel and Google Sheets are used worldwide to organize and analyze data, but getting the right information into them isn’t always straightforward. Businesses often need ...

Why write SQL queries when you can get an LLM to write the code for you? Query NFL data using querychat, a new chatbot component that works with the Shiny web framework and is compatible with R and ...

Your browser does not support the audio element. Pandas is a Python library used for data analysis and manipulation on labeled datasets. The core mission of the ...

Guidance works with most open-source LMs that can be hosted locally. Fundamentally different from conventional prompting techniques, Guidance enforces constraints by steering the model token by token ...

The Cloud SQL Python Connector is a Cloud SQL connector designed for use with the Python language. Using a Cloud SQL connector provides a native alternative to the Cloud SQL Auth Proxy while providing ...

The National Cyber Security Centre provides details on prompt injection and data poisoning attacks so organizations using machine-learning models can mitigate the risks. Large language models used in ...