In the field of machine learning, model accuracy is paramount, yet achieving an optimal balance between overfitting and underfitting…

This is part of the Data Engineering Roadmap.

When working with large datasets or long-running tasks in Python, parallel processing can save you time and improve performance. Generators…

Using Retrieval Augmented Generation (RAG) on my content to create a bot that answers using my knowledge

This code uses the openpyxl library to read and write Excel files. It defines two functions get_info and write_info, and a main function to…

Explore how these powerful tools can work together to optimize your code

Discover how to optimize your code with these powerful Python techniques

Boost Your Productivity Through Effective Memory Management and Lazy Evaluation

The buffer protocol in Python provides a way to access the internal data of an object. This protocol is a lower-level interface that allows…

If you work with Python’s generators, you know how useful they are for handling large datasets and streams of data. Generators allow you to…

Discover how these language features can elevate your Python programming skills

Generators and context managers are powerful tools in Python that can help you write more efficient and readable code. In this article…

Discover how combining generators and async/await enhances concurrent tasks handling

How to save, share, and manage Versions of Code Assets such as Notebooks and saved Queries

Exploring the Versatility of Generators

This article compares Entropy Pooling (EP) to the Black-Litterman (BL) model.

Explore how these powerful tools can streamline your code and boost efficiency

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using requests, beautiful soup and pandas.

Another day, another period of time where I tinker and experiment with code.