Alternatives to Theano logo

Alternatives to Theano

TensorFlow, MXNet, Keras, Torch, and Caffe are the most popular alternatives and competitors to Theano.
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What is Theano and what are its top alternatives?

Theano is a Python library that lets you to define, optimize, and evaluate mathematical expressions, especially ones with multi-dimensional arrays (numpy.ndarray). Using Theano it is possible to attain speeds rivaling hand-crafted C impleme
Theano is a tool in the Machine Learning Tools category of a tech stack.
Theano is an open source tool with 9.2K GitHub stars and 2.5K GitHub forks. Here鈥檚 a link to Theano's open source repository on GitHub

Top Alternatives of Theano

Theano alternatives & related posts

related TensorFlow posts

Conor Myhrvold
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber | 7 upvotes 831.1K views

Why we built an open source, distributed training framework for TensorFlow , Keras , and PyTorch:

At Uber, we apply deep learning across our business; from self-driving research to trip forecasting and fraud prevention, deep learning enables our engineers and data scientists to create better experiences for our users.

TensorFlow has become a preferred deep learning library at Uber for a variety of reasons. To start, the framework is one of the most widely used open source frameworks for deep learning, which makes it easy to onboard new users. It also combines high performance with an ability to tinker with low-level model details鈥攆or instance, we can use both high-level APIs, such as Keras, and implement our own custom operators using NVIDIA鈥檚 CUDA toolkit.

Uber has introduced Michelangelo (https://eng.uber.com/michelangelo/), an internal ML-as-a-service platform that democratizes machine learning and makes it easy to build and deploy these systems at scale. In this article, we pull back the curtain on Horovod, an open source component of Michelangelo鈥檚 deep learning toolkit which makes it easier to start鈥攁nd speed up鈥攄istributed deep learning projects with TensorFlow:

https://eng.uber.com/horovod/

(Direct GitHub repo: https://github.com/uber/horovod)

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StackShare Editors
StackShare Editors

In mid-2015, Uber began exploring ways to scale ML across the organization, avoiding ML anti-patterns while standardizing workflows and tools. This effort led to Michelangelo.

Michelangelo consists of a mix of open source systems and components built in-house. The primary open sourced components used are HDFS, Spark, Samza, Cassandra, MLLib, XGBoost, and TensorFlow.

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MXNet logo

MXNet

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A flexible and efficient library for deep learning
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    MXNet logo
    MXNet
    VS
    Theano logo
    Theano
    Keras logo

    Keras

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    Deep Learning library for Theano and TensorFlow
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    Keras
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    Theano

    related Keras posts

    Conor Myhrvold
    Conor Myhrvold
    Tech Brand Mgr, Office of CTO at Uber | 7 upvotes 831.1K views

    Why we built an open source, distributed training framework for TensorFlow , Keras , and PyTorch:

    At Uber, we apply deep learning across our business; from self-driving research to trip forecasting and fraud prevention, deep learning enables our engineers and data scientists to create better experiences for our users.

    TensorFlow has become a preferred deep learning library at Uber for a variety of reasons. To start, the framework is one of the most widely used open source frameworks for deep learning, which makes it easy to onboard new users. It also combines high performance with an ability to tinker with low-level model details鈥攆or instance, we can use both high-level APIs, such as Keras, and implement our own custom operators using NVIDIA鈥檚 CUDA toolkit.

    Uber has introduced Michelangelo (https://eng.uber.com/michelangelo/), an internal ML-as-a-service platform that democratizes machine learning and makes it easy to build and deploy these systems at scale. In this article, we pull back the curtain on Horovod, an open source component of Michelangelo鈥檚 deep learning toolkit which makes it easier to start鈥攁nd speed up鈥攄istributed deep learning projects with TensorFlow:

    https://eng.uber.com/horovod/

    (Direct GitHub repo: https://github.com/uber/horovod)

    See more

    I am going to send my website to a Venture Capitalist for inspection. If I succeed, I will get funding for my StartUp! This website is based on Django and Uses Keras and TensorFlow model to predict medical imaging. Should I use Heroku or PythonAnywhere to deploy my website ?? Best Regards, Adarsh.

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    Torch logo

    Torch

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    An open-source machine learning library and a script language based on the Lua programming language
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      Torch logo
      Torch
      VS
      Theano logo
      Theano
      Caffe logo

      Caffe

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      A deep learning framework
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        Caffe logo
        Caffe
        VS
        Theano logo
        Theano
        PyTorch logo

        PyTorch

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        A deep learning framework that puts Python first
        PyTorch logo
        PyTorch
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        Theano

        related PyTorch posts

        Conor Myhrvold
        Conor Myhrvold
        Tech Brand Mgr, Office of CTO at Uber | 7 upvotes 831.1K views

        Why we built an open source, distributed training framework for TensorFlow , Keras , and PyTorch:

        At Uber, we apply deep learning across our business; from self-driving research to trip forecasting and fraud prevention, deep learning enables our engineers and data scientists to create better experiences for our users.

        TensorFlow has become a preferred deep learning library at Uber for a variety of reasons. To start, the framework is one of the most widely used open source frameworks for deep learning, which makes it easy to onboard new users. It also combines high performance with an ability to tinker with low-level model details鈥攆or instance, we can use both high-level APIs, such as Keras, and implement our own custom operators using NVIDIA鈥檚 CUDA toolkit.

        Uber has introduced Michelangelo (https://eng.uber.com/michelangelo/), an internal ML-as-a-service platform that democratizes machine learning and makes it easy to build and deploy these systems at scale. In this article, we pull back the curtain on Horovod, an open source component of Michelangelo鈥檚 deep learning toolkit which makes it easier to start鈥攁nd speed up鈥攄istributed deep learning projects with TensorFlow:

        https://eng.uber.com/horovod/

        (Direct GitHub repo: https://github.com/uber/horovod)

        See more
        NumPy logo

        NumPy

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        Fundamental package for scientific computing with Python
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        NumPy
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        Theano
        Numba logo

        Numba

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        An open source JIT compiler that translates a subset of Python and NumPy code into fast machine code
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          Numba logo
          Numba
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          Theano logo
          Theano