Networks

How you can improve training beyond the “vanilla” gradient descent algorithmIn my last post, we discussed how you possibly can improve the performance of neural networks through hyperparameter tuning:This can be a process whereby...

How you possibly can improve the “learning” and “training” of neural networks through tuning hyperparametersEach hidden-layer neuron carries out the next computation:

An example of predicting bulk density (RHOB) with Keras and illustrating impacts of normalisation on prediction results11 min read·16 hours agoLarge amounts of information are acquired each day from wells around the globe. Nevertheless,...

Within the ever-evolving world of artificial intelligence (AI), scientists have recently heralded a big milestone. They've crafted a neural network that exhibits a human-like proficiency in language generalization. This groundbreaking development isn't only a...

An Introductory GuideIn this text, I would love to elucidate my journey in developing a model for automatic harmonic evaluation. Personally, I'm curious about understanding music deeply. Questions like: “Why are things structured the...

A graph-based approach to modeling the spread of knowledge through social networksSocial media has completely revolutionized the data landscape. We're more connected to every aside from now we have every been in human history....

A Python example using diagnostic input variablesAnd, so on and so forth, until all crosstabs between parent-child pairs are defined.Now, most BNs include many parent-child relationships, so calculating probabilities can get tedious (and majorly...

As Vice President of Software Engineering, Doug is chargeable for all elements of the Cornelis Networks’ software stack, including the Omni-Path Architecture drivers, messaging software, and embedded device control systems. Before joining Cornelis Networks,...