Summary of Pytorch vs Tensorflow vs Keras | Deep Learning Tutorial 6 (Tensorflow Tutorial, Keras & Python)
Summary of Main Ideas
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Overview of Frameworks
- The video discusses the differences between three popular deep learning frameworks: PyTorch, TensorFlow, and Keras.
- PyTorch is developed by Facebook, while TensorFlow is developed by Google.
- A lesser-known framework, CNTK (Microsoft Cognitive Toolkit), is mentioned but is not as popular as the first two.
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Understanding Keras
- Keras is not a full-fledged deep learning framework like PyTorch and TensorFlow; instead, it serves as a high-level wrapper around these frameworks (as well as CNTK and Theano).
- The purpose of Keras is to simplify the coding experience for users who find direct programming in TensorFlow or CNTK challenging.
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Integration of Keras with TensorFlow
- With the introduction of TensorFlow 2.0, Keras has been integrated into the TensorFlow library, allowing users to access Keras functionalities directly from TensorFlow.
- There is no need to install Keras separately; it is included within TensorFlow.
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Code Snippets
- The video includes code snippets demonstrating how to import and use Keras within TensorFlow.
- Previously, Keras allowed users to specify different backends (like CNTK or Theano), but the tutorial focuses on using TensorFlow as the backend.
Methodology/Instructions
- Installation
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Using Keras with TensorFlow
- Import Keras directly from TensorFlow instead of installing it separately.
- Use the convenient APIs provided by Keras integrated within TensorFlow for deep learning tasks.
Speakers/Sources Featured
- The speaker is not explicitly named in the subtitles, but they are providing a tutorial on deep learning frameworks. The frameworks discussed are:
- PyTorch (by Facebook)
- TensorFlow (by Google)
- Keras (as a wrapper around TensorFlow, CNTK, and Theano)
- CNTK (Microsoft Cognitive Toolkit)
- Theano (not as prominently featured)
Notable Quotes
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Category
Educational