Gradient Descent Explained with Python: Math, Visualization, and Code
Learn how gradient descent minimizes a loss function. Derive the gradients, code it in NumPy, and test learning rates with a plotted experiment.
Xray AI Lab
Learn how gradient descent minimizes a loss function. Derive the gradients, code it in NumPy, and test learning rates with a plotted experiment.
Learn linear algebra for machine learning: vectors, dot products, matrix multiplication, and eigenvalues, with runnable NumPy examples and PCA.
Learn real-time object detection with YOLO in Python: bounding boxes, confidence scores, video inference, and tracking objects across frames.
Learn image segmentation with Segment Anything (SAM) in Python: point and box prompts, masks, bounding boxes, automatic mode, and honest limitations.
Vector RAG vs Graph RAG compared: what the papers found, the trade-offs, and a small reproducible Python experiment on multi-hop retrieval.
Learn how vision-language models work: image encoders, CLIP embeddings, captioning, and visual question answering, with a runnable Python demo.
Learn how machine learning detects cyber threats, from supervised models to anomaly detection, with a runnable Python example and honest limits.
Learn how Retrieval-Augmented Generation (RAG) works, why it outperforms basic LLMs for custom data, and how to build a working RAG app in Python.
Learn how AI agents work, explore real-world applications, compare top frameworks, and build a simple AI agent with Python.
Learn to build an AI agent with Python step by step. Set up your environment, implement tool calling, run the project, and troubleshoot common errors.