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scikit-learn vs Tensorpack: What are the differences?
scikit-learn: Easy-to-use and general-purpose machine learning in Python. scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license; Tensorpack: A neural network training interface based on TensorFlow. It is a Neural Net Training Interface on TensorFlow, with focus on speed + flexibility. It is a training interface based on TensorFlow, which means: you’ll use mostly tensorpack high-level APIs to do training, rather than TensorFlow low-level APIs.
scikit-learn and Tensorpack can be primarily classified as "Machine Learning" tools.
scikit-learn and Tensorpack are both open source tools. scikit-learn with 40K GitHub stars and 19.5K forks on GitHub appears to be more popular than Tensorpack with 5.36K GitHub stars and 1.64K GitHub forks.
Pros of scikit-learn
- Scientific computing25
- Easy19
Pros of Tensorpack
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Cons of scikit-learn
- Limited2