Unit 2 PJOK kelas 6 membahas permainan net seperti bola voli dan bulu tangkis yang menekankan akurasi pukulan, koordinasi gerak, dan strategi penempatan bola Materi ini dirancang untuk mengasah ...
KERAS 3.0 RELEASED A superpower for ML developers Keras is a deep learning API designed for human beings, not machines. Keras focuses on debugging speed, code elegance & conciseness, maintainability, and deployability. When you choose Keras, your codebase is smaller, more readable, easier to iterate on.
Getting started with Keras Learning resources Are you a machine learning engineer looking for a Keras introduction one-pager? Read our guide Introduction to Keras for engineers. Want to learn more about Keras 3 and its capabilities? See the Keras 3 launch announcement. Are you looking for detailed guides covering in-depth usage of different parts of the Keras API? Read our Keras developer ...
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
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. Flexible – Keras adopts the principle of progressive disclosure of complexity: simple workflows should be quick and ...
Keras documentation: Code examples Our code examples are short (less than 300 lines of code), focused demonstrations of vertical deep learning workflows.