Keras is an open-source neural network library written in Python, designed to enable fast experimentation with deep learning models. It provides a user-friendly interface for building and training neural networks, supporting both convolutional and recurrent networks, as well as combinations of the two. Keras runs on top of TensorFlow, Theano, or CNTK backends.
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About Keras
Keras was created in 2015 by François Chollet, a Google engineer. It was developed to provide a high-level interface for building and experimenting with deep learning models quickly and efficiently. The library aimed to simplify the complexity of implementing neural networks, making it accessible to a wider audience of researchers and developers.
Strengths of Keras include its user-friendly API, rapid prototyping capabilities, and strong community support. Weaknesses involve limited flexibility for highly customized models and potential performance overhead compared to lower-level frameworks. Competitors include TensorFlow, PyTorch, and MXNet.
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How to hire a Keras expert
A Keras expert must have strong proficiency in Python programming, a deep understanding of neural network architectures, and experience with TensorFlow backend. They should also be skilled in data preprocessing, model evaluation, and hyperparameter tuning. Knowledge of advanced deep learning techniques such as transfer learning and model optimization is essential.
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