serengil/tensorflow-101 resource

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1099 stars · 627 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A collection of Jupyter notebooks and Python scripts teaching deep learning with TensorFlow and Keras through hands-on projects. It covers face recognition, facial expression recognition, style transfer, autoencoders, and transfer learning with step-by-step tutorials and pre-trained model weights.

Use cases

• learn deep learning with tensorflow from scratch
• build a facial expression recognition model
• implement face recognition with vgg-face or facenet
• understand transfer learning and autoencoders with code examples
• follow step-by-step cnn tutorials with documentation
• run real-time emotion analysis on video

When to choose

• you want tutorial-style deep learning code with explanations
• you are learning TensorFlow/Keras through computer vision projects
• you need reference implementations of face recognition models

When to avoid

• you need a production-ready face recognition library (use deepface instead)
• you want a maintained framework rather than educational notebooks
• you need frameworks other than TensorFlow/Keras

Facets

learning-resource · maturity active

machine-learning deep-learning image-processing computer-vision deep-learning computer-vision tutorials education python tensorflow keras jupyter-notebooks face-recognition facial-expression-recognition style-transfer autoencoders transfer-learning convolutional-neural-networks vgg-face facenet step-by-step-tutorial

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