Machine Learning Platforms
There are many methods for doing automated Machine Learning. Early methods modeled biological or statistical building blocks in low level procedural code. The programming methodologies have evolved over the years to have libraries of the building blocks built and packaged for convenience. Even at a higher level, whole platforms have been packaged and provided in such a way that almost drag and drop methods can be used, with parameter choice made at different levels of automation.
Languages
Python
R
SQL
SAS
others (C/C++, java, etc.)
Libraries
Tensorflow (Google)
Keras
CoreML (Apple)
https://machinelearning.apple.com/
https://developer.apple.com/machine-learning
OpenCV
Pandas
Scikit-learn
MxNet
Big Data Platforms
CUDA (Program on NVIDIA GPUs)
Hadoop (Cluster management using MapReduce algorithm)
Spark/Skala (New cluster management)
Cloud Services
(most available on-prem as well)
DataScience.com
DataRobot
Ersatz
Alteryx
C3iot.ai
H2O.ai
IBM Watson