Monitor performance issues & errors in your code

Top 10 machine learning libraries

Episode #131, published Tue, Sep 26, 2017, recorded Thu, Jul 20, 2017

Data science has been one of the major driving forces behind the explosion of Python in recent years. It's now used for AI research, controls some of the most powerful telescopes in the world, tracks crop growth and prediction and so much more.

But with all this growth, there is an explosion of data science and machine learning libraries. That's why I invited Pete Garcin onto the show. He's going to share his top 10 machine learning libraries. After this episode, you should be able to pick the right one for the job.
Links from the show

Pete on Twitter: @rawktron
Pete on GitHub: github.com/rawktron
ActivePython: activestate.com/activepython
NeuroBlast AI Game: github.com/ActiveState/neuroblast

The 10 Machine Learning Libraries
Numpy/Scipy: numpy.org
Scikit-Learn: scikit-learn.org
Keras: keras.io
TensorFlow: tensorflow.org
Theano: deeplearning.net/software/theano
Pandas: pandas.pydata.org
Caffe/Caffe 2: caffe.berkeleyvision.org
Jupyter: jupyter.org
CNTK: microsoft.com/en-us/cognitive-toolkit
NLTK: nltk.org
Episode transcripts: talkpython.fm

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