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Keras
What is Keras?
Keras is an open-source deep learning framework written in Python that provides a high-level neural network API to enable fast experimentation and easy transition from research prototype to production. The user-friendly API of Keras makes it simple to quickly prototype, train, and deploy neural network and deep learning models across a variety of platforms including TensorFlow, JAX, and PyTorch.
Who Uses Keras?
Deep learning solution for any individual interested in machine learning with features such as modularity, neural layers, module extensibility, and Python coding support.
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Reviews of Keras
What you need definitely to start your deep learning experiments
Comments: I would defintely recommend it as the quickest step to start testing your model.
Pros:
Keras is the only platform that runs on top of most popular backends like TensorFlow, pyTorch and Microsoft Cogntitive Toolkit. This gives great flexibility to researchers to try their network architecture with minimal changes across multiple libraries mentioned. The sequencing modularity is what makes you build sophisticated network with improved code readability .
Cons:
If you encounter an error, it is hard to be debugged.
Keras for deep learning
Comments: I did many deep learning projects using keras it is really helpful
Pros:
easy to use, large communities and support
Cons:
keras has many predefined methods and functions but it is difficult to integrate a custom class.
Keras for school project
Pros:
I did use this library couple of times during the semester to solve my deep learning course home works and project. compared to tensor flow it was easier for me to use
Cons:
It was not still easy to use and well documented with examples
Great Deeplearning framework
Comments: i use keras for image classification making use of it's pretrained architectures especially the resnet architectures.
Pros:
What i love most about keras is it's wrapper functions, i use it to perform Gridsearch using scikitlearn and this is amazing as i cannot do this on other frameworks. keras also has a good documentation page with lots of pretrained CNN architectures for image classifications solutions.
Cons:
Nothing to dislike about this framework yet.
Start Learning From Keras Framework
Comments: I recommend it for performing image classification as it provides some inbuilt fucntionality for image preprocessing. It even comes with many usefull pre-trained models like resnet.
Pros:
First thing i like about Keras is that it runs on the top of tensorflow background. Deep learning and neural network construction and visulaization is simple using Keras, also it comes with enough documentations. It provides lots of inbuilt functions for image processing which makes it lots easier for image classificaiton.
Cons:
For building more customized deep learning model, you need to use TensorFlow. Also the model inferencing time is little slow compared to model directly build in TensorFlow.
