H2O vs PredictionIO vs scikit-learn

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H2O

100
160
+ 1
4
PredictionIO

66
100
+ 1
5
scikit-learn

834
885
+ 1
32
Decisions about H2O, PredictionIO, and scikit-learn

A large part of our product is training and using a machine learning model. As such, we chose one of the best coding languages, Python, for machine learning. This coding language has many packages which help build and integrate ML models. For the main portion of the machine learning, we chose PyTorch as it is one of the highest quality ML packages for Python. PyTorch allows for extreme creativity with your models while not being too complex. Also, we chose to include scikit-learn as it contains many useful functions and models which can be quickly deployed. Scikit-learn is perfect for testing models, but it does not have as much flexibility as PyTorch. We also include NumPy and Pandas as these are wonderful Python packages for data manipulation. Also for testing models and depicting data, we have chosen to use Matplotlib and seaborn, a package which creates very good looking plots. Matplotlib is the standard for displaying data in Python and ML. Whereas, seaborn is a package built on top of Matplotlib which creates very visually pleasing plots.

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Pros of H2O
Pros of PredictionIO
Pros of scikit-learn
  • 1
    Highly customizable
  • 1
    Very fast and powerful
  • 1
    Auto ML is amazing
  • 1
    Super easy to use
  • 5
    Predict Future
  • 18
    Scientific computing
  • 14
    Easy

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Cons of H2O
Cons of PredictionIO
Cons of scikit-learn
  • 1
    Not very popular
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    • 1
      Limited

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    What is H2O?

    H2O.ai is the maker behind H2O, the leading open source machine learning platform for smarter applications and data products. H2O operationalizes data science by developing and deploying algorithms and models for R, Python and the Sparkling Water API for Spark.

    What is PredictionIO?

    PredictionIO is an open source machine learning server for software developers to create predictive features, such as personalization, recommendation and content discovery.

    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.

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    What companies use H2O?
    What companies use PredictionIO?
    What companies use scikit-learn?

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    What tools integrate with H2O?
    What tools integrate with PredictionIO?
    What tools integrate with scikit-learn?
      No integrations found

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      What are some alternatives to H2O, PredictionIO, and scikit-learn?
      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.
      DataRobot
      It is an enterprise-grade predictive analysis software for business analysts, data scientists, executives, and IT professionals. It analyzes numerous innovative machine learning algorithms to establish, implement, and build bespoke predictive models for each situation.
      Keras
      Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
      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.
      CUDA
      A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
      See all alternatives
      Reviews of H2O, PredictionIO, and scikit-learn
      Review of
      PredictionIO

      PredictionIO is an open source Machine Learning Server. It empowers programmers and data engineers to build smart applications. Machine Learning is about attempting to teach computers to predict future, or otherwise unknown events, by applying computer science or statistics techniques to analyze existing data. It can be seen as a transformation from existing data to improve insights about the unknown. PredictionIO is useful for any web and mobile apps. Here are some examples of smart features you can build with PredictionIO: predict user behaviors; offer personalized video, news, deals, ads and job openings; help users to discover interesting events, documents, apps and restaurants; provide impressive match-making services, etc.

      How developers use H2O, PredictionIO, and scikit-learn
      Dolls Kill uses
      PredictionIO

      We run eCommerce product recommendations using predictionIO machine learning techniques