Alternatives to Chainer logo

Alternatives to Chainer

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

It is an open source deep learning framework written purely in Python on top of Numpy and CuPy Python libraries aiming at flexibility. It supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort.
Chainer is a tool in the Machine Learning Tools category of a tech stack.
Chainer is an open source tool with 5.3K GitHub stars and 1.4K GitHub forks. Here’s a link to Chainer's open source repository on GitHub

Chainer alternatives & related posts

Keras logo

Keras

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Deep Learning library for Theano and TensorFlow
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Keras
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Chainer

related Keras posts

Conor Myhrvold
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 6 upvotes · 562.1K views
atUber TechnologiesUber Technologies
TensorFlow
TensorFlow
Keras
Keras
PyTorch
PyTorch

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‚ÄĒfor instance, we can use both high-level APIs, such as Keras, and implement our own custom operators using NVIDIA‚Äôs 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‚Äôs deep learning toolkit which makes it easier to start‚ÄĒand speed up‚ÄĒdistributed deep learning projects with TensorFlow:

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

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

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TensorFlow logo

TensorFlow

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Open Source Software Library for Machine Intelligence
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TensorFlow
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Chainer

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Conor Myhrvold
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 6 upvotes · 562.1K views
atUber TechnologiesUber Technologies
TensorFlow
TensorFlow
Keras
Keras
PyTorch
PyTorch

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‚ÄĒfor instance, we can use both high-level APIs, such as Keras, and implement our own custom operators using NVIDIA‚Äôs 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‚Äôs deep learning toolkit which makes it easier to start‚ÄĒand speed up‚ÄĒdistributed deep learning projects with TensorFlow:

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

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

See more
StackShare Editors
StackShare Editors
| 4 upvotes · 82.4K views
atUber TechnologiesUber Technologies
Cassandra
Cassandra
Apache Spark
Apache Spark
TensorFlow
TensorFlow

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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PyTorch logo

PyTorch

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

related PyTorch posts

Conor Myhrvold
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber · | 6 upvotes · 562.1K views
atUber TechnologiesUber Technologies
TensorFlow
TensorFlow
Keras
Keras
PyTorch
PyTorch

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‚ÄĒfor instance, we can use both high-level APIs, such as Keras, and implement our own custom operators using NVIDIA‚Äôs 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‚Äôs deep learning toolkit which makes it easier to start‚ÄĒand speed up‚ÄĒdistributed deep learning projects with TensorFlow:

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

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

See more
Theano logo

Theano

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Define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently
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    Theano
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    Chainer
    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
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      Chainer
      Caffe logo

      Caffe

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      A deep learning framework
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        Caffe
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        Chainer
        scikit-learn logo

        scikit-learn

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        Easy-to-use and general-purpose machine learning in Python
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        scikit-learn
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        Chainer
        ML Kit logo

        ML Kit

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        Machine learning for mobile developers (by Google)
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          CUDA logo

          CUDA

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          It provides everything you need to develop GPU-accelerated applications
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            TensorFlow.js logo

            TensorFlow.js

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            Machine Learning in JavaScript
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            TensorFlow.js
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            H2O logo

            H2O

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            H2O.ai AI for Business Transformation
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              PredictionIO logo

              PredictionIO

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              Open Source Machine Learning Server
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              PredictionIO
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              NLTK logo

              NLTK

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              It is a leading platform for building Python programs to work with human language data
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                Caffe2 logo

                Caffe2

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                Open Source Cross-Platform Machine Learning Tools (by Facebook)
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                Kubeflow logo

                Kubeflow

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                Machine Learning Toolkit for Kubernetes
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                  .NET for Apache Spark logo

                  .NET for Apache Spark

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                  Makes Apache Spark‚ĄĘ Easily Accessible to .NET Developers
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                    Pipelines logo

                    Pipelines

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                    Machine Learning Pipelines for Kubeflow
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                      Microsoft Cognitive Services logo

                      Microsoft Cognitive Services

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                      APIs, SDKs, and services available to help developers build intelligent applications
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                        MLflow logo

                        MLflow

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                        An open source machine learning platform
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                          Stan logo

                          Stan

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                          A Probabilistic Programming Language
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