GitHub

cv2.imread() from 16-bit TIFF creates arrays where np.maximum() fails in function context but works directly

Platform: macOS-15.6.1 (arm64) Python 3.14.2 OpenCV: 4.11.0 NumPy: 2.2.6 cv2.imread() with 16-bit TIFF files creates float32 arrays that cause np.maximum() and np.minimum() to behave inconsistently.
GitHub

100_Numpy_exercises.md

This is a collection of exercises that have been collected in the numpy mailing list, on stack overflow and in the numpy documentation. The goal of this collection is to offer a quick reference for ...
Visual Studio Magazine

Binary Classification Using LightGBM

Dr. James McCaffrey from Microsoft Research presents a full-code, step-by-step tutorial on using the LightGBM tree-based system to perform binary classification (predicting a discrete variable that ...
Visual Studio Magazine

Multi-Class Classification Using a scikit Decision Tree

Decision trees are useful for relatively small datasets that have a relatively simple underlying structure, and when the trained model must be easily interpretable, explains Dr. James McCaffrey of ...
nptelegraph

From the Pulpit: Do we need to attend church to have a relationship with God?

I have heard it more than a few times in my life. There may have even been a time when I said it. “I do not need to attend church to have a relationship with God.” Perhaps lack of church attendance is ...
marktechpost

Logistic Regression With A Real-World Example in Python

In this tutorial, you will learn Python Logistic Regression. Here you’ll know what exactly is Logistic Regression and you’ll also see an Example with Python. Logistic Regression is an important topic ...