In Pyper, the task decorator is used to transform functions into composable pipelines. Let's simulate a pipeline that performs a series of transformations on some data.

You can apply a Processor to any input stream and easily iterate through its output stream: The concept of Processor provides a common abstraction for Gemini model calls and increasingly complex ...

Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your ...

Abstract: A three-way clustering algorithm based on image processing is proposed by combining blurring and sharpening operations in digital image processing. The proposed algorithm quantifies the ...

Overview: NumPy is ideal for data analysis, scientific computing, and basic ML tasks.PyTorch excels in deep learning, GPU ...