Creating CGI HTTP Server with http.server.CGIHTTPRequestHandler

The simple plumbing behind dynamic web applications

A simple to-do list web app with a Python and Flask server backend. The server provides GET and POST API endpoints for managing items with JSON. The front-end uses vanilla JavaScript with fetch and async/await to dynamically update the DOM and perform optimistic updates for a fast UI.
Implementing Convolutional Neural Networks with tf.keras.layers.Conv2D

Implementing Convolutional Neural Networks with tf.keras.layers.Conv2D

Keras Conv2D parameters for optimal CNN performance. Analysis of kernel_size, filters, padding, and BatchNormalization. Also covers efficient SeparableConv2D layers and kernel_regularizer to combat overfitting. This approach improves accuracy, speed, and training stability in your network.