TensorFlow2.0-Examples

Why we included this project

The TensorFlow 2.x API changed enough that many older tutorials no longer run as written, so working code in the new API is worth more than another pass over the theory. This collection covers each topic with both a Jupyter notebook and a standalone Python script, ranging from basic tensor operations up through convolutional networks, YOLOv3 object detection, U-Net and FCN8s segmentation, and generative models like DCGAN and pix2pix. The examples stay small and readable, which makes them useful as a baseline to adapt for your own task or to trace how a model fits together. It is organized as a study path rather than a production toolkit, so treat it as a learning resource and a place to borrow patterns from instead of a library to drop into a deployed system.