Neural
Artificial Intelligence
Hyperparameter Tuning: Neural Networks 101
How you possibly can improve the “learning” and “training” of neural networks through tuning hyperparametersEach hidden-layer neuron carries out the next computation:
Artificial Intelligence
Using AI to optimize for rapid neural imaging
Connectomics, the ambitious field of study that seeks to map the intricate...
Artificial Intelligence
Well Log Measurement Prediction Using Neural Networks with Keras
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,...
Artificial Intelligence
Neural Networks Achieve Human-Like Language Generalization
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...
Artificial Intelligence
Roman Numeral Evaluation with Graph Neural Networks
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...
Artificial Intelligence
The Best Optimization Algorithm for Your Neural Network
Learn how to select it and minimize your neural network training time.The above cycle is repeated multiple times until satisfactory performance levels are achieved. The “experiment” phase involves each the coding and the training...
Artificial Intelligence
Discovering Differential Equations with Physics-Informed Neural Networks and Symbolic Regression
A case study with step-by-step code implementation25 min read·11 hours agoSuch partial knowledge of the governing differential equations hinders our understanding and control of those dynamical systems. Consequently, inferring these unknown components based on...
Artificial Intelligence
Recurrent Neural Networks, Explained and Visualized from the Ground Up Complex Flavors of Recurrent Networks Neural Machine Translation Text-Output Recurrent Models Bidirectionality Autoregressive Generation 2016 Google Translate
The design of the Recurrent Neural Network (1985) is premised upon two observations about how a great model, similar to a human reading text, would process sequential information:It should track the data ‘learned’ up...
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