Five Python Libraries for Machine Learning ๐
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It is an open-source library created by the Google Brain team.
It is very popular for high-performance numerical computation.
It has an ecosystem of tools, libraries, and community resources for building and deploying powerful ML applications.
It is an open-source library created by the Google Brain team.
It is very popular for high-performance numerical computation.
It has an ecosystem of tools, libraries, and community resources for building and deploying powerful ML applications.
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Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow.
It is a high-level neural networks API capable of running on top of TensorFlow, CNTK, or Theano.
It can run seamlessly on both CPU and GPU.
Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow.
It is a high-level neural networks API capable of running on top of TensorFlow, CNTK, or Theano.
It can run seamlessly on both CPU and GPU.
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Pandas is also an open-source library.
It is a very fast, powerful, and easy-to-use data analysis and manipulation tool.
It is not directly related to Machine Learning.
As we know that the dataset must be prepared before training.
Pandas is also an open-source library.
It is a very fast, powerful, and easy-to-use data analysis and manipulation tool.
It is not directly related to Machine Learning.
As we know that the dataset must be prepared before training.
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Pytorch is also an open-source library.
It is based on the torch library which is implemented in C with a wrapper in Lua.
It has a big choice of tools and libraries that can be used for NLP, Computer Vision, etc.
Pytorch is also an open-source library.
It is based on the torch library which is implemented in C with a wrapper in Lua.
It has a big choice of tools and libraries that can be used for NLP, Computer Vision, etc.
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Scikit-learn provides a range of supervised and unsupervised learning algorithms via a consistent interface in Python.
It is licensed under a permissive simplified BSD license encouraging academic and commercial use.
Scikit-learn provides a range of supervised and unsupervised learning algorithms via a consistent interface in Python.
It is licensed under a permissive simplified BSD license encouraging academic and commercial use.
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