Which framework is better for deep learning implementation? What is the advantage and disadvantage of everyone?

Question

I'm a beginner at deep learning and I don't know which framework is better? Tensorflow? PyTorch? Chainer? ....

Answer 1

Scikit-Learn’s

Scikit Learn is easy to use for developers to perform general-purpose machine learning algorithms both supervised and unsupervised learning. Scikit learn provide the easily implementation of classic algorithm like Classification ( Support Vector Machine), Regression, Clustering. But the Scikit Learn doesn’t provide the machine-learning algorithm Neural Networks implementation. It also doesn’t provide the GPU support.

Caffe

Caffe is basically a first production deep learning library but it isn’t very flexible. Building block layers are complex and also require large capacity to perform operations. If you want to support CPU and GPU, you need to implement extra functions and you have to define your model in plane text editor. Caffe’s main architect now working for Tensorflow’s team.

Keras

Lets talk about the Keras. Keras provide very high level of apis’ to build deep learning models. Keras uses object oriented design where every thing is considered as an object. All the functionalities like: Models ,Optimisers and Outputs can get called through object oriented property. It has a great documentation and wide range of support.

Theano

Theano has multiple documentations and native windows support. Theano is no longer be maintained and one other disadvantage is compiling complex symbolic graphs can be slow.

TensorFlow

Tensorflow is just growing so fast whatever new features in machine learning it implements rapidly fast in Tensorflow, you can also view the activity on github repo. Since its scale better across the multiple GPUs. However, a better alternative if you want to learn and get your hand dirty with deep learning is “TF Learn” which is basically Keras but optimise in Tensorflow. So the best library to use for research is Tensorflow. The world class researchers like OpenAi and DeepMind are now using the Tensorflow and for production the best library is still to use is Tensorflow.