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Keras vs TensorFlow vs PyTorch : Comparison of the Deep Learning Frameworks

Last updated on May 22,2019 12.4K Views
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A Data Science Enthusiast with in-hand skills in programming languages such as... A Data Science Enthusiast with in-hand skills in programming languages such as Java & Python.

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Keras, TensorFlow and PyTorch are among the top three frameworks that are preferred by Data Scientists as well as beginners in the field of  Deep Learning.This comparison on Keras vs TensorFlow vs PyTorch will provide you with a crisp knowledge about the top Deep Learning Frameworks and help you find out which one is suitable for you. In this blog you will get a complete insight into the above three frameworks in the following sequence:

Introduction

Keras

keras - Edureka

Keras is an open source neural network library written in Python. It is capable of running on top of TensorFlow. It is designed to enable fast experimentation with deep neural networks.

TensorFlow

TensorFlow - Edureka

TensorFlow is an open-source software library for dataflow programming across a range of tasks. It is a symbolic math library that is used for machine learning applications like neural networks.

PyTorch

PyTorch - Edureka

PyTorch is an open source machine learning library for Python, based on Torch. It is used for applications such as natural language processing and was developed by Facebook’s AI research group.

Keras vs Tensorflow vs PyTorch | Edureka

Comparison Factors

All the three frameworks are related to each other and also have certain basic differences that distinguishes them from one another.

So lets have a look at the parameters that distinguish them:

Level of API

Level of API - Edureka

Keras is a high-level API capable of running on top of TensorFlow, CNTK and Theano. It has gained favor for its ease of use and syntactic simplicity, facilitating fast development.

TensorFlow is a framework that provides both high and low level APIs. Pytorch, on the other hand, is a lower-level API focused on direct work with array expressions. It has gained immense interest in the last year, becoming a preferred solution for academic research, and applications of deep learning requiring optimizing custom expressions.

Speed

Speed - Edureka

The performance is comparatively slower in Keras whereas Tensorflow and PyTorch provide a similar pace which is fast and suitable for high performance.

Architecture

Architecture - Edureka

Keras has a simple architecture. It is more readable and concise . Tensorflow on the other hand is not very easy to use even though it provides Keras as a framework that makes work easier. PyTorch has a complex architecture and the readability is less when compared to Keras.

Debugging

Debugging - front end developer skills - edureka

In keras, there is usually very less frequent need to debug simple networks. But in case of Tensorflow, it is quite difficult to perform debugging. Pytorch on the other hand has better debugging capabilities as compared to the other two.

Dataset

Dataset - Edureka

Keras is usually used for small datasets as it is comparitively slower. On the other hand, TensorFlow and PyTorch are used for high performance models and large datasets that require fast execution.

Popularity

Popularity - Edureka

With the increasing demand in the field of Data Science, there has been an enormous growth of Deep learning technology in the industry. With this, all the three frameworks have gained quite a lot of popularity. Keras tops the list followed by TensorFlow and PyTorch. It has gained immense popularity due to its simplicity when compared to the other two.

Get in-depth Knowledge of Deep Learning

These were the parameters that distinguish all the three frameworks but there is no absolute answer to which one is better. The choice ultimately comes down to 

  • Technical background
  • Requirements and
  • Ease of Use

Final Verdict

Now coming to the final verdict of Keras vs TensorFlow vs PyTorch let’s have a look at the situations that are most preferable for each one of these three deep learning frameworks

keras - Edureka

Keras is most suitable for:

  • Rapid Prototyping
  • Small Dataset
  • Multiple back-end support
TensorFlow - Edureka

TensorFlow is most suitable for:

PyTorch - Edureka

PyTorch is most suitable for:

  • Flexibility
  • Short Training Duration
  • Debugging capabilities

Now with this, we come to an end of this comparison on Keras vs TensorFlow vs PyTorch. I Hope you guys enjoyed this article and understood which Deep Learning Framework is most suitable for you.

Now that you have understood the comparison between Keras, TensorFlow and PyTorch, check out the AI and Deep Learning With Tensorflow by Edureka, a trusted online learning company with a network of more than 250,000 satisfied learners spread across the globe. This Certification Training is curated by industry professionals as per the industry requirements & demands. You will master concepts such as SoftMax function, Autoencoder Neural Networks, Restricted Boltzmann Machine (RBM) and work with libraries like Keras & TFLearn.

Got a question for us? Please mention it in the comments section of “Keras vs TensorFlow vs PyTorch” and we will get back to you.

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