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scikit-learn

1.2K
1.1K
+ 1
44
Tensorpack

2
7
+ 1
0
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scikit-learn vs Tensorpack: What are the differences?

scikit-learn: Easy-to-use and general-purpose machine learning in Python. scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license; Tensorpack: A neural network training interface based on TensorFlow. It is a Neural Net Training Interface on TensorFlow, with focus on speed + flexibility. It is a training interface based on TensorFlow, which means: you’ll use mostly tensorpack high-level APIs to do training, rather than TensorFlow low-level APIs.

scikit-learn and Tensorpack can be primarily classified as "Machine Learning" tools.

scikit-learn and Tensorpack are both open source tools. scikit-learn with 40K GitHub stars and 19.5K forks on GitHub appears to be more popular than Tensorpack with 5.36K GitHub stars and 1.64K GitHub forks.

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Pros of scikit-learn
Pros of Tensorpack
  • 25
    Scientific computing
  • 19
    Easy
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    Cons of scikit-learn
    Cons of Tensorpack
    • 2
      Limited
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      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.

      What is Tensorpack?

      It is a Neural Net Training Interface on TensorFlow, with focus on speed + flexibility. It is a training interface based on TensorFlow, which means: you’ll use mostly tensorpack high-level APIs to do training, rather than TensorFlow low-level APIs.

      Need advice about which tool to choose?Ask the StackShare community!

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      What companies use Tensorpack?
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        What tools integrate with scikit-learn?
        What tools integrate with Tensorpack?

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        What are some alternatives to scikit-learn and Tensorpack?
        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.
        Keras
        Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/
        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.
        XGBoost
        Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow
        Apache Spark
        Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
        See all alternatives