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Episode #131: Top 10 machine learning libraries

Published Tues, Sep 26, 2017, recorded Thurs, 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

Want to go deeper? Check out my courses

Pete Garcin
Pete Garcin
Pete Garcin is Developer Evangelist @ActiveState. Pete has over 15 years in software development in both web and games having shipped over 40 titles in roles ranging from Programmer to Audio Director to Executive Producer. He earned his undergraduate degree at University of Waterloo, and an MA in Communication from Carleton University in Ottawa. He’s passionate about engaging with communities and dedicated to enhancing developers’ experiences with ActiveState products.


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