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A Python Machine Learning project to classify the Iris Dataset

Jupyter Notebook 100.00%
iris-dataset iris-classification python3 machinelearning machine-learning kmeans-clustering svm svm-classifier regression linear-regression logistic-regression decision-trees randomforest random-forest random-forest-classifier gridsearchcv randomizedsearchcv exploratory-data-analysis datavisualization

iris-species-classification's Introduction

Iris Species Prediction

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This project was created for an INSAID (International School of AI and Data Science) term project (Term 4 - Intermediate Machine Learning) to predict the species of the Iris Dataset

A brief overview of the project:

  1. EDA
  2. Train-Test-Split
  3. Scaling of Data
  4. Linear Regression
  5. Logistic Regression
  6. Regression using Decision Trees (including Gridsearch CV)
  7. Regression using Random Forests (including Randomized Search CV)
  8. Naive Bayes Classification
  9. K Means Clustering
  10. SVM Classification
  11. Model Evaluation

To check out my notebook, please click here

To find me on Github, please click here

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iris-species-classification's People

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