# YunYang1994/TensorFlow2.0-Examples

🙄 Difficult algorithm, Simple code.

Repository: https://github.com/YunYang1994/TensorFlow2.0-Examples
Canonical: https://ross.abutalabs.com/products/tensorflow20-examples
Language: Jupyter Notebook
License: MIT
License Family: permissive
Topics: tensorflow2, tensorflow-examples, deep-learning, deep-neural-networks, machine-learning, gan, linear-regression, resnet, reinforcement-learning, image-classification, object-detection, convolutional-neural-network, pix2pix, dcgan-tensorflow, vgg16, yolov3, unet-image-segmentation, fcn8s, tensorflow
Last push: 2023-03-25T00:21:23+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 2736, "days_push": 1258, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1699, forks 661 (observed 2026-08-28T04:05:24.131338+00:00)

## What it is
A collection of TensorFlow 2.0 tutorials and example implementations covering deep learning fundamentals through advanced models like YOLOv3, GANs, ResNet, and U-Net. It provides Jupyter notebooks and source code with explanations for learning TensorFlow 2.0.

## Use cases
- learn tensorflow 2.0 from examples
- understand how yolov3 is implemented
- study gan implementations like dcgan and pix2pix
- learn image segmentation with unet and fcn
- get started with gradienttape and automatic differentiation
- implement resnet and vgg16 from scratch
- learn reinforcement learning basics in tensorflow

## When to choose
- you want readable, minimal code examples to learn TensorFlow 2.0
- you need reference implementations of classic vision models like YOLOv3, ResNet, or U-Net
- you prefer learning through notebooks with explanations

## When to avoid
- you need production-ready or actively maintained model code
- you use PyTorch or a framework other than TensorFlow
- you need the latest TensorFlow 2.x APIs, as the repo is no longer frequently updated

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: machine-learning, deep-learning, image-processing, computer-vision
- domain: deep-learning, machine-learning, computer-vision, tutorials
- platform: python
- tags: tensorflow2, jupyter-notebooks, yolov3, gan, resnet, unet, image-segmentation, object-detection, reinforcement-learning, educational

## Member repositories
- YunYang1994/TensorFlow2.0-Examples (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:24.131338+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:37:47.520793+00:00, confidence not recorded.
  - readme: https://github.com/YunYang1994/TensorFlow2.0-Examples (fetched 2026-08-28T04:05:24.131338+00:00, sha 4485437f3fad)
- Data as of 2026-08-30T08:39:29.467469+00:00.