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01_​Simple_​Neural_​Network

Workflow

Simple Neural Network

Introduction to Machine Learning Algorithms course - Session 3
Exercise 1
- Train a fully connected neural network
- Apply the trained network to the test set
- Evaluate the mode performance with the Scorer node



educationneural networkmachine learning
Classification: Simple Neural Network Exercise: Simple Neural Network1) Train a fully connected neural network using the RProp MLP Learner node.2) Apply the model to the test set and evaluate the model (MultiLayerPerceptron Predictor node and Scorer node) 3) Optional: Build a paramter optimization loop to optimize the number of layers and the number of neurons per layer. Read AmesHousing.csvCSV Reader Preprocessing Classification: Simple Neural Network Exercise: Simple Neural Network1) Train a fully connected neural network using the RProp MLP Learner node.2) Apply the model to the test set and evaluate the model (MultiLayerPerceptron Predictor node and Scorer node) 3) Optional: Build a paramter optimization loop to optimize the number of layers and the number of neurons per layer. Read AmesHousing.csvCSV Reader Preprocessing

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Resources

Nodes

01_​Simple_​Neural_​Network consists of the following 21 nodes(s):

Plugins

01_​Simple_​Neural_​Network contains nodes provided by the following 2 plugin(s):