

Keras
Overview :
Keras is a human-centric API designed with best practices in mind. It simplifies the cognitive load by offering a consistent and straightforward API that minimizes user interaction for common use cases. It also provides clear and actionable error messages. Keras aims to give developers who want to launch machine learning-based applications an unfair advantage. Keras prioritizes debugging speed, code elegance and conciseness, maintainability, and deployability. With Keras, your codebase becomes smaller, more readable, and easier to iterate on. Your models run faster with the support of XLA compilation and Autograph optimization, and they are easier to deploy across various platforms (servers, mobile devices, browsers, embedded devices).
Target Users :
Keras is suitable for various deep learning tasks, including image recognition, natural language processing, speech recognition, and more. It can be used for research, prototyping, and production deployment.
Use Cases
Building an image classification model with Keras
Performing sentiment analysis with Keras
Generating text with Keras
Features
Provides a simple, flexible, and powerful API for building deep learning models
Supports rapid prototyping and deployment
Built on the TensorFlow platform, scalable to large-scale GPU clusters or entire TPU pods
Easy to deploy to various platforms, including browsers, mobile devices, and embedded devices
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