PyTorch vs scikit-learn vs TransmogrifAI

PyTorch

631
668
+ 1
18
scikit-learn

684
673
+ 1
29
TransmogrifAI

4
15
+ 1
0
Advice on PyTorch, scikit-learn, and TransmogrifAI
Adithya Shetty
Student at PES UNIVERSITY · | 5 upvotes · 40K views
Needs advice
on
TensorFlow
PyTorch
and
Keras

I have just started learning some basic machine learning concepts. So which of the following frameworks is better to use: Keras / TensorFlow/PyTorch. I have prior knowledge in python(and even pandas), java, js and C. It would be nice if something could point out the advantages of one over the other especially in terms of resources, documentation and flexibility. Also, could someone tell me where to find the right resources or tutorials for the above frameworks? Thanks in advance, hope you are doing well!!

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      What is 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.

      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.

      What is TransmogrifAI?

      TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library for building modular, reusable, strongly typed machine learning workflows on Spark with minimal hand tuning
      What companies use PyTorch?
      What companies use scikit-learn?
      What companies use TransmogrifAI?

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      What tools integrate with PyTorch?
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      What are some alternatives to PyTorch, scikit-learn, and TransmogrifAI?
      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.
      Keras
      Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
      Caffe2
      Caffe2 is deployed at Facebook to help developers and researchers train large machine learning models and deliver AI-powered experiences in our mobile apps. Now, developers will have access to many of the same tools, allowing them to run large-scale distributed training scenarios and build machine learning applications for mobile.
      MXNet
      A deep learning framework designed for both efficiency and flexibility. It allows you to mix symbolic and imperative programming to maximize efficiency and productivity. At its core, it contains a dynamic dependency scheduler that automatically parallelizes both symbolic and imperative operations on the fly.
      Torch
      It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.
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