Alternatives to PySyft logo

Alternatives to PySyft

PyTorch, TensorFlow, scikit-learn, Keras, and ML Kit are the most popular alternatives and competitors to PySyft.
3
3
+ 1
0

What is PySyft and what are its top alternatives?

It is a Python library for secure and private Deep Learning. PySyft decouples private data from model training, using Federated Learning, Differential Privacy, and Multi-Party Computation (MPC) within the main Deep Learning frameworks like PyTorch and TensorFlow.
PySyft is a tool in the Machine Learning Tools category of a tech stack.
PySyft is an open source tool with 5K GitHub stars and 1.1K GitHub forks. Here鈥檚 a link to PySyft's open source repository on GitHub

PySyft alternatives & related posts

PyTorch logo

PyTorch

355
353
11
355
353
+ 1
11
A deep learning framework that puts Python first
PyTorch logo
PyTorch
VS
PySyft logo
PySyft

related PyTorch posts

Conor Myhrvold
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber | 6 upvotes 595.9K 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
TensorFlow logo

TensorFlow

1.4K
1.4K
62
1.4K
1.4K
+ 1
62
Open Source Software Library for Machine Intelligence
TensorFlow logo
TensorFlow
VS
PySyft logo
PySyft

related TensorFlow posts

Conor Myhrvold
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber | 6 upvotes 595.9K 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
StackShare Editors
StackShare Editors
| 4 upvotes 99.8K 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.

!

See more
scikit-learn logo

scikit-learn

485
403
24
485
403
+ 1
24
Easy-to-use and general-purpose machine learning in Python
scikit-learn logo
scikit-learn
VS
PySyft logo
PySyft
Keras logo

Keras

483
404
11
483
404
+ 1
11
Deep Learning library for Theano and TensorFlow
Keras logo
Keras
VS
PySyft logo
PySyft

related Keras posts

Conor Myhrvold
Conor Myhrvold
Tech Brand Mgr, Office of CTO at Uber | 6 upvotes 595.9K 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
ML Kit logo

ML Kit

123
164
0
123
164
+ 1
0
Machine learning for mobile developers (by Google)
    Be the first to leave a pro
    ML Kit logo
    ML Kit
    VS
    PySyft logo
    PySyft
    CUDA logo

    CUDA

    88
    47
    0
    88
    47
    + 1
    0
    It provides everything you need to develop GPU-accelerated applications
      Be the first to leave a pro
      CUDA logo
      CUDA
      VS
      PySyft logo
      PySyft
      TensorFlow.js logo

      TensorFlow.js

      77
      147
      6
      77
      147
      + 1
      6
      Machine Learning in JavaScript
      TensorFlow.js logo
      TensorFlow.js
      VS
      PySyft logo
      PySyft
      H2O logo

      H2O

      55
      57
      0
      55
      57
      + 1
      0
      H2O.ai AI for Business Transformation
        Be the first to leave a pro
        H2O logo
        H2O
        VS
        PySyft logo
        PySyft