{"id":1698,"date":"2022-03-23T19:12:29","date_gmt":"2022-03-23T19:12:29","guid":{"rendered":"https:\/\/jenniferkwentoh.com\/?p=1698"},"modified":"2022-06-01T15:54:14","modified_gmt":"2022-06-01T15:54:14","slug":"keras-vs-tensorflow-vs-pytorch-which-is-better-or-easier","status":"publish","type":"post","link":"https:\/\/jenniferkwentoh.com\/keras-vs-tensorflow-vs-pytorch-which-is-better-or-easier\/","title":{"rendered":"Keras vs TensorFlow vs PyTorch | Which is Better or Easier?"},"content":{"rendered":"\n

Keras, TensorFlow, and PyTorch are some of the most popular machine learning and deep learning frameworks<\/a> being used by professionals and newbies alike. <\/p>\n\n\n\n

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.<\/p>\n\n\n\n

What is TensorFlow?<\/h2>\n\n\n\n
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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.<\/p>\n\n\n\n

TensorFlow was originally developed by Google Brain team and released as open source software in November 2015.<\/p>\n\n\n\n

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.<\/a><\/p>\n\n\n\n

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.<\/p>\n\n\n\n

The core TensorFlow framework provides APIs for expressing parallel computations, training models and executing them on both CPUs and GPUs.<\/p>\n\n\n\n

What is Keras?<\/h2>\n\n\n\n

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.<\/mark><\/p>\n\n\n\n

\"machine_learning_libraries_keras_logo\"<\/figure><\/div>\n\n\n\n

Going from idea to result with the least possible delay allows for faster iteration during the development process, which leads to better models. <\/p>\n\n\n\n

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. <\/p>\n\n\n\n

Keras has the following key features:<\/h3>\n\n\n\n