Python Code for NN and DL – Alianna J. Maren

Transition to Object-Oriented Python for the Cluster Variation Method

July 23, 2018 AJMaren Comments 3 comments

The Cluster Variation Method – A Topographic Approach: Object-oriented programming is essential for working with the Cluster Variation Method (CVM), especially if we’re going to insert a CVM layer into a neural network. The reason is that approaching free energy minima via changing node states requires dealing with node, net, and grid topographies. If we’re going to be at all strategic in moving towards free energy minima, then we can’t just pick nodes at random. We need to know…

Labor Day Reading and Academic Year Kick-Off

August 30, 2017 AJMaren Comments 9 comments

Deep Learning / Machine Learning Reading and Study Guide: Several of you have been asking for guided reading lists. This makes sense. Your Starting Point for Neural Networks, Deep Learning, and Machine Learning Your study program (reading and code) depends on where you are. Starting out (High-grass country; St. Louis to Alcove Springs): Basic neural networks and deep learning; architecture for common networks, such as CNNs (convolutional neural networks); learning rules and architecture design. Well on the…

Neural Networks and Python Code: Be Careful with the Array Indices!

January 12, 2017 AJMaren Comments 5 comments

Our Special Topics class on Deep Learning (Northwestern University, Master of Science in Predictive Analytics program, Winter, 2017) starts off with very basic neural networks: the backpropagation learning method applied to the classic X-OR problem. I’m writing Python code to go with this class, and the result by the end of the quarter should be five-to-six solid pieces of code, involving either the backpropagation or Boltzmann machine learning algorithm, with various network configurations. The following figure shows the dependence of…

Alianna J. Maren

Statistical Mechanics, Neural Networks, Artificial Intelligence

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