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What is Keras?
Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research.
Keras focuses on debugging speed, code elegance & conciseness, maintainability, and deployability. It prioritizes providing users with consistent & simple APIs, minimizing the number of actions required for common tasks, and offering clear & actionable error messages, along with comprehensive documentation and developer guides.
Features
- Cross-framework compatibility: Works with JAX, TensorFlow, and PyTorch.
- User-friendly API: Designed for human beings, with consistent and simple APIs.
- Reduced cognitive load: Minimizes user actions for common use cases.
- Clear error messages: Provides actionable feedback for debugging.
- Excellent documentation: Offers comprehensive documentation and developer guides.
- Scalability: Can scale to large clusters of GPUs or an entire TPU pod.
- Research-friendly: Offers low-level flexibility for implementing research ideas.
- Fast Experimentation: Speed up experimentation cycles
Use Cases
- Rapid prototyping of deep learning models.
- Developing and deploying machine learning applications.
- Conducting state-of-the-art research in deep learning.
- Building models that can be used across different frameworks (JAX, TensorFlow, PyTorch).
- Scaling machine learning workflows to large datasets and compute resources.
- Deploying models to various platforms (server, mobile, browser, embedded).
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