Simple Sample Codes for Iris Dataset Classification

This is a collection of simple and easy-to-read program, for Iris dataset classification. These are some different types of libraries available so that you can see the implementation difference between one and another for the same usage.

Check another dataset: Palmer Penguin Dataset which is slightly more complex than Iris dataset

Required Packages

Please install requirements.txt file in each folder

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Keras (using Tensorflow backend)

• Simple Neural Net for Iris dataset using Keras (Multilayer perceptron model, with one hidden layer)

Lasagne

• Simple Neural Net for Iris dataset using Lasagne (Multilayer perceptron model, with one hidden layer)

Python

• Simple Neural Net for Iris dataset without external library (Multilayer perceptron model, with one hidden layer)
• Simple Neural Net for Iris dataset without external library (No-hidden layer model)
• Simple Neural Net for Iris dataset using Scikit-learn-MLPClassifier (Multilayer perceptron model, with one hidden layer)
• Simple Neural Net for Iris dataset using Scikit-learn Random Forest

PyTorch

• Simple Neural Net for Iris dataset using PyTorch (Multilayer perceptron model, with one hidden layer)

Tensorflow

• Simple Neural Net for Iris dataset using Tensorflow (Multilayer perceptron model, with one hidden layer)
• Simple Neural Net for Iris dataset using Tensorflow Estimator (Multilayer perceptron model, with one hidden layer)
• Simple Neural Net for Iris dataset using Tensorflow version 2.x (Multilayer perceptron model, with one hidden layer)