Keras, TensorFlow, and PyTorch are some of the most popular machine learning and deep learning frameworks being used by professionals and newbies alike.
Deep learning is a subset of machine learning that uses neural networks to train models on large datasets. This compares three popular Deep Learning Frameworks: Keras, TensorFlow, and PyTorch. Here you’ll find key differences between these frameworks and will be able to decide which would be best for you.
What is TensorFlow?
TensorFlow is an open-source software library for machine learning research and development. It provides a set of tools for numerical computation using data flow graphs.
TensorFlow was originally developed by Google Brain team and released as open source software in November 2015.
It is used for machine learning applications, including speech recognition, image recognition, predictive analytics, natural language processing, and other more specialized tasks. See Tensorflow Lite for Android.
TensorFlow was originally developed to support the development of machine learning models, but the scope of TensorFlow has since been expanded to include other types of modeling and data processing.
The core TensorFlow framework provides APIs for expressing parallel computations, training models and executing them on both CPUs and GPUs.
What is Keras?
Keras is an open-source neural network high-level API that can run on top of TensorFlow, Theano or CNTK. It was written in Python, developed with the intention to allow for fast experimentation.
Going from idea to result with the least possible delay allows for faster iteration during the development process, which leads to better models.
Keras’s backend can be configured to use Theano or TensorFlow. This means that it can be used with one or the other without worrying about switching between them, making it easier for developers who want to experiment with different deep learning frameworks without rewriting their code.
Keras has the following key features:
- Support for convolutional neural networks (CNN) for computer vision applications, recurrent neural networks (RNN) for sequence processing applications, and any combination.
- High level of customizability through user-defined callbacks and hooks.
- Support for arbitrary network architectures: multi-input or multi-output models are easily expressed in just a few lines of code.
Keras has two main components:
The first is a high-level API to build and train deep learning models. This API makes it easy to quickly prototype new ideas without getting bogged down in the details of building neural networks. The second is a set of pre-built models that can be used for common tasks such as classification, regression, clustering, and more.
What is PyTorch?
PyTorch is a deep learning framework that provides GPU acceleration and support for both Python and C++. It is one of the most popular frameworks in the deep learning space, with an active community of developers.
PyTorch was developed by Meta’s artificial intelligence research group, which also created Caffe2, a machine learning framework.
The first public release of PyTorch was in January 2016.
Keras vs TensorFlow vs PyTorch what is the difference?
These three frameworks have a lot in common, although they are all slightly different.
|1. Architecture||simpler and more readable architecture||complex architecture|
|2. API||provides both high and low level APIs||High level||Low Level|
|3. Speed||fast||comparatively slower||super fast|
|4. Backend||No backend needed||Backend support include TensorFlow, Theano, CNTK||No backend needed|
|5. Dataset||can crunch large datasets with high performance||suitable for small datasets||can crunch large datasets with high performance|
TensorFlow vs Keras vs PyTorch Which is Easier for Beginners?
These frameworks have different learning curves. Because of Keras’s simplicity, it’s easier to understand.
Keras vs TensorFlow vs PyTorch Which is Better?
Keras is perfect for programming quick prototypes and things that need to be created without a lot of data.
PyTorch is most suitable for building large models with big data and high performance.
Keras vs TensorFlow vs PyTorch Which is Faster?
PyTorch is comparatively faster than Keras.
PyTorch vs Keras vs TensorFlow Which is more popular?
According to Quora and Kaggle, Keras seems to be the most popular deep learning framework among data scientists for its simplicity and PyTorch by academia and industrial research team for research flexibility.