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Pythia vs scikit-learn: What are the differences?
Developers describe Pythia as "Framework for vision and language multimodal research". A modular framework for supercharging vision and language research built on top of PyTorch. On the other hand, scikit-learn is detailed as "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.
Pythia and scikit-learn can be categorized as "Machine Learning" tools.
Pythia and scikit-learn are both open source tools. It seems that scikit-learn with 36K GitHub stars and 17.6K forks on GitHub has more adoption than Pythia with 2.6K GitHub stars and 310 GitHub forks.
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- Scientific computing25
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What is Pythia?
A modular framework for supercharging vision and language research built on top of PyTorch.
What is scikit-learn?
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
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What are some alternatives to Pythia and scikit-learn?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
Keras
Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
CUDA
A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
Streamlit
It is the app framework specifically for Machine Learning and Data Science teams. You can rapidly build the tools you need. Build apps in a dozen lines of Python with a simple API.