Perceptrons
Perceptron is a machine learning algorithm that helps to provide classified outcomes for computing. It is a kind of a single-layer artificial network with only one neuron and a classification algorithm that makes its predictions based on a linear predictor function combining a set of weights with the feature vector.
Multilayer Perceptron
Multilayer Perceptron is a class of feed forward artificial neural networks. And the layered feed forward networks are trained by using the static back-propagation training algorithm. For designing and training an MLP perceptron several issues are involved:
- Number of hidden layers is selected to use in the neural network.
- A solution that avoids local minima is globally searched.
- Neural networks are validated to test for overfitting.
- Converging to an optimal solution in a reasonable period of time.
- Backpropagation algorithm for the on-line training of Multilayer Perceptrons
- Multilayer Perceptrons and Kemel Networks
- Multilayer Perceptron Neural Network for flow prediction
- Probability matching in Perceptrons
Related Conference of Perceptrons
September 10-11, 2024
7th International Conference on Artificial Intelligence, Machine Learning and Robotics
Amsterdam, Netherlands
October 24-25, 2024
10th World Congress on Computer Science, Machine Learning and Big Data
Zurich, Switzerland
November 25-26, 2024
10th International Conference and Expo on Computer Graphics & Animation
Vancouver, Canada
Perceptrons Conference Speakers
Recommended Sessions
- Ambient Intelligence
- Artificial Intelligence
- Artificial Neural Networks
- Autonomous Robots
- Backpropagation
- Bioinformatics
- Cloud Computing
- Cognitive Computing
- Computational Creativity
- Deep Learning
- Entrepreneurs Investment Meet
- Natural Language Processing
- Parallel Processing
- Perceptrons
- Self-Organizing Neural Networks
- Support Vector Machines
- Ubiquitous Computing