Keras vs Tensorflow | Deep Learning Frameworks Comparison | Intellipaat
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In this video on keras vs tensorflow you will understand about the top deep learning frameworks used in the IT industry, and which one should you use for better performance. So in this keras vs tensorflow comparison some important parameters have been taken into consideration to tell you the difference between keras and tensorflow also which one is preferred over the other in certain aspects in detail.
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📝Following topics are covered in this Keras vs Tensorflow comparison tutorial:
01:35 - What is Keras?
02:03 - What is Tensorflow?
02:40 - Differentiating between Keras and Tensorflow
05:21 - Benifits of using Keras
06:05 - Benifits of using Tensorflow
06:45 - Limitation of using Keras
07:45 - Limitation of using Tensorflow
09:00 - Popularity and trends in Keras and Tensorflow
10:00 - Which is better to choose?
11:40 -Quiz
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What do you think which one of them is better among Tensorflow vs Keras according to you? Tell us in the comment section below.
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Why Keras is important
Keras is an Open Source Neural Network library written in Python that runs on top of Theano or Tensorflow. It is designed to be modular, fast and easy to use. Keras is very quick to make a network model. If you want to make a simple network model with a few lines, Keras can help you with that.
Why Tensorflow is important
TensorFlow is an open source machine learning framework for carrying out high-performance numerical computations. It provides excellent architecture support which allows easy deployment of computations across a variety of platforms ranging from desktops to clusters of servers, mobiles, and edge devices.
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