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Learn MorePros of Keras
Pros of Stack Overflow
Pros of Keras
- Quality Documentation8
- Supports Tensorflow and Theano backends7
- Easy and fast NN prototyping7
Pros of Stack Overflow
- Scary smart community257
- Knows all206
- Voting system142
- Good questions134
- Good SEO83
- Addictive22
- Tight focus14
- Share and gain knowledge10
- Useful7
- Fast loading3
- Gamification2
- Knows everyone1
- Experts share experience and answer questions1
- Stack overflow to developers As google to net surfers1
- Questions answered quickly1
- No annoying ads1
- No spam1
- Fast community response1
- Good moderators1
- Quick answers from users1
- Good answers1
- User reputation ranking1
- Efficient answers1
- Leading developer community1
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Cons of Keras
Cons of Stack Overflow
Cons of Keras
- Hard to debug4
Cons of Stack Overflow
- Not welcoming to newbies3
- Unfair downvoting3
- Unfriendly moderators3
- No opinion based questions3
- Mean users3
- Limited to types of questions it can accept2
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What is Keras?
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
What is Stack Overflow?
Stack Overflow is a question and answer site for professional and enthusiast programmers. It's built and run by you as part of the Stack Exchange network of Q&A sites. With your help, we're working together to build a library of detailed answers to every question about programming.
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What companies use Keras?
What companies use Stack Overflow?
What companies use Keras?
What companies use Stack Overflow?
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What tools integrate with Keras?
What tools integrate with Stack Overflow?
What tools integrate with Keras?
What tools integrate with Stack Overflow?
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What are some alternatives to Keras and Stack Overflow?
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
MXNet
A deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, it contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly.
Postman
It is the only complete API development environment, used by nearly five million developers and more than 100,000 companies worldwide.
Postman
It is the only complete API development environment, used by nearly five million developers and more than 100,000 companies worldwide.