Electron microscopy
  
Comparison between scikit-learn and tensorflow
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Table 4349. Comparison between scikit-learn and tensorflow.

scikit-learn tensorflow
Higher-level library Low-level library

"off-the-shelf" algorithms, which is ready to use algorithms

A library for constructing Neural Networks

Is intended to work with tabular data

Can work with a variety of data types: tabular, text, images, audio

MLPClassifier and MLPRegressor available for classic Multi-Layer implementation

  

Much faster

 Much slower
Is mainly used for machine learning Is mainly used for deep learning
Can be used for classification such as SVMs, Random Forests, Logistic Regression and so on Can be used to implement machine learning algorithms
Includes implementations of several machine learning algorithms Allows to build machine learning models (and other computations) using a set of simple operators, like “add”, “matmul”, “concat”, etc.
Can be used ot define a model object in a single line or a few lines of code, then use it to fit a set of points or predict a value. Allows to take advantage of GPUs for more efficient training
Can do many different kinds of Regression and Classification Can be used to do Regression and Classification
Less popular More popular

 

         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         
         

 

 

 

 

 

 

 

 

 

 
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