Alternatives to ML Kit logo

Alternatives to ML Kit

TensorFlow, scikit-learn, Keras, PyTorch, and CUDA are the most popular alternatives and competitors to ML Kit.
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What is ML Kit and what are its top alternatives?

ML Kit brings Google鈥檚 machine learning expertise to mobile developers in a powerful and easy-to-use package.
ML Kit is a tool in the Machine Learning Tools category of a tech stack.

ML Kit alternatives & related posts

TensorFlow logo

TensorFlow

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Open Source Software Library for Machine Intelligence
TensorFlow logo
TensorFlow
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ML Kit logo
ML Kit

related TensorFlow posts

Conor Myhrvold
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber | 6 upvotes 591.9K 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
| 4 upvotes 97.9K 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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scikit-learn logo

scikit-learn

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

Keras

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Deep Learning library for Theano and TensorFlow
Keras logo
Keras
VS
ML Kit logo
ML Kit

related Keras posts

Conor Myhrvold
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber | 6 upvotes 591.9K 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
PyTorch logo

PyTorch

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A deep learning framework that puts Python first
PyTorch logo
PyTorch
VS
ML Kit logo
ML Kit

related PyTorch posts

Conor Myhrvold
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber | 6 upvotes 591.9K 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
CUDA logo

CUDA

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It provides everything you need to develop GPU-accelerated applications
    Be the first to leave a pro
    CUDA logo
    CUDA
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    ML Kit logo
    ML Kit
    TensorFlow.js logo

    TensorFlow.js

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    Machine Learning in JavaScript
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    TensorFlow.js
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    ML Kit
    H2O logo

    H2O

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    H2O.ai AI for Business Transformation
      Be the first to leave a pro
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      H2O
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      ML Kit logo
      ML Kit
      PredictionIO logo

      PredictionIO

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      Open Source Machine Learning Server
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      PredictionIO
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      ML Kit