KERAS an app that helps to analyze a large volume of data .pptx
- 4. High-level neural networks API, written in Python Models described in Python code. No separate models config files Allows for easy and fast prototyping (through user friendliness, modularity, and extensibility) Runs seamlessly on CPUs and GPUs
- 6. Keras is an Application Programme Interface designed for human beings, not machines. It puts user experience front and center. Keras follows best practices for reducing cognitive load (amount of working memory resources used): it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear and actionable feedback upon user error.
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- 9. Buildasimplemodel In Keras, you assemble layers to build models. A model is (usually) a graphof layers. Themost commontype of model isastack of layers: the model. Tobuildasimple, fully-connected network (i.e., amulti-layerperceptron):
- 12. Keras is a high-level API to build and train deep learning models. It’s used for fast prototyping, advanced research, and production, with three key advantages: User friendly – Keras has a simple, consistent interface optimized for common use cases. It provides clear and actionable feedback for user errors. Modular and composable – Keras models are made by connecting configurable building blocks together, with few restrictions. Easy to extend – Write custom building blocks to express new ideas for research. Create new layers, loss functions, and develop state-of-the-art models.