Why Shifting to the Object-Oriented Coding Approach REALLY IS Important: Well, I hate having to admit it. Mud on my face; all that. But I made a pretty significant Whoops! back this last winter when I posted a “Verification and Validation” document (hah!) to arXiv. The Sad Story of My Previous Ineptitude Well, there’s nothing like hearing about someone else’s screw-up in order to make us feel better about our own life, so here goes. I’d…
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…
New Code (Not Released Yet): V&V the Code Before We Play: Well, my darling, as you gathered from last week’s post, the world has shifted. Up until now, when we were talking about having a new free energy function to use inside a neural network, we had to do “Gedankenexperiments” (German for “thought experiments”). Now, though, there’s working code – and I so LOVE seeing the numbers and graphs come out; teasing it, playing with it … stroking it…
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…
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…