Machine learning, data mining framework briefly summarize the relevant

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Artificial Intelligence in python hottest, bias related to deep learning artificial intelligence, neural network learning;
machine learning from a very early knowledge of statistics, data mining also comes from this;

Machine Learning Related:

Distributed expansion TensorFlow :( work production, using small devices like mobile phones into the element)

Referred to as tf, specifically, the depth of learning, the use of the GPU, a high degree of freedom, the cost of higher learning, has expanded to a traditional machine learning, version 2.0 simplifies the API will be a lot more comfortable, conducive to the deployment of distributed production; (with keras, simplifying API use)

pychor :( personal research, learning)

2018 newborn machine learning, learning portal approachable, benchmarking TensorFlow, do individuals learn to use, API high degree of abstraction, for small and medium-scale, distributed deployment might also like extension;

scikit-learn :( classic algorithm)

python third-party libraries, for small and medium data, the classic stand-alone machine learning algorithms, non-depth, like neural networks can use the tool library.

spark ml :( big data cluster analysis scenarios, by cpu, memory extended)

Is the scene spark ecosystem-related part of machine learning for a spark distributed big data technology stack