Revision as of 16:33, 15 March 2020

Basics

A process by which an algorythm can produce other algorhythms, code, and even CAD based off of training data, and training
many methods each with their own advantages
One near essential application is complex problems such as autonomous navigation, problem solving, object recognition, etc
Being software, there are many open source tools
Main requirements are Training Data
Can create solutions to problems humans could never make
Can sometimes be hard to explain the core of the "method" it comes up with
See the CPG Grey Video On It
Can be a buzzword so keep that in mind when reading headlines etc
NEED EXPERT EXPLAINING

@@ Line 8: / Line 8: @@
 *Can sometimes be hard to explain the core of the "method" it comes up with
 *See the [https://www.youtube.com/watch?v=R9OHn5ZF4Uo CPG Grey Video On It]
+*Can be a buzzword so keep that in mind when reading headlines etc
 *NEED EXPERT EXPLAINING
 =See Also=
-*
+*[[TensorFlow]]
+*[[Accord.NET]]
+*[[Knime]]
+*[[Shogun (Software) ]]
+*[[Mlpack]]
+*[[Oryx 2]]
+*[[Eclipse Deeplearning4j]]
+*[[Scikit-learn]]
+*[[Veles]]
+*[[Nervana Neo]]
 =Useful Links=
 *[https://en.wikipedia.org/wiki/Machine_learning The Wikipedia Page on Machine Learning]
+*[https://www.youtube.com/watch?v=R9OHn5ZF4Uo A Video by the youtbe channel CPG Grey Video On It]
+*[https://towardsdatascience.com/10-must-try-open-source-tools-for-machine-learning-1c4420ef40df A Website Listing various Open Source Tools]