- Keras: Deep Learning for humans
Keras is a deep learning API designed for human beings, not machines Keras focuses on debugging speed, code elegance conciseness, maintainability, and deployability
- Getting started with Keras
Read our Keras developer guides Are you looking for tutorials showing Keras in action across a wide range of use cases? See the Keras code examples: over 150 well-explained notebooks demonstrating Keras best practices in computer vision, natural language processing, and generative AI
- Keras 3 API documentation
Keras Applications Xception EfficientNet B0 to B7 EfficientNetV2 B0 to B3 and S, M, L ConvNeXt Tiny, Small, Base, Large, XLarge VGG16 and VGG19 ResNet and ResNetV2 MobileNet, MobileNetV2, and MobileNetV3 DenseNet NasNetLarge and NasNetMobile InceptionV3 InceptionResNetV2
- Code examples - Keras
All of our examples are written as Jupyter notebooks and can be run in one click in Google Colab, a hosted notebook environment that requires no setup and runs in the cloud Google Colab includes GPU and TPU runtimes ★ = Good starter example V3 = Keras 3 example
- About Keras 3
About Keras 3 Keras is a deep learning API written in Python and capable of running on top of either JAX, TensorFlow, or PyTorch Keras is: Simple – but not simplistic Keras reduces developer cognitive load to free you to focus on the parts of the problem that really matter
- Developer guides - Keras
They're one of the best ways to become a Keras expert Most of our guides are written as Jupyter notebooks and can be run in one click in Google Colab, a hosted notebook environment that requires no setup and runs in the cloud
- Keras Applications
Keras Applications are deep learning models that are made available alongside pre-trained weights These models can be used for prediction, feature extraction, and fine-tuning
- Introduction to Keras for engineers
Introduction Keras 3 is a deep learning framework works with TensorFlow, JAX, and PyTorch interchangeably This notebook will walk you through key Keras 3 workflows
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