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@@ -6,7 +6,7 @@ Different ML Techniques on the Iris dataset. For more information, see [this](ht
 
 ### About the data
 
-Iris dataset is a multivariate data set with 150 samples and 4 features. The data set is named after the iris plant. The data set is loaded from [this](https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data) link. It comes pre-installed with the Python package `sklearn`. 
+Iris dataset is a multivariate data set with 150 samples and 4 features. The data set is named after the iris plant. The data set is loaded from [this](https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data) link. It comes pre-installed with the Python package `sklearn`. We have obtained the data set from [this](https://www.kaggle.com/uciml/iris) Kaggle link.
 
 
 ### Features
@@ -15,9 +15,48 @@ The data set contains the following features:
 
 | Feature | Description |
 | --- | --- |
-| sepal length in cm | the length of the sepals |
-| sepal width in cm | the width of the sepals |
-| petal length in cm | the length of the petals |
-| petal width in cm | the width of the petals |
+| Id | The id of the sample |
+| SepalLengthCm | the length of the sepals |
+| SepalWidthCm | the width of the sepals |
+| PetalLengthCm | the length of the petals |
+| PetalWidthCm | the width of the petals |
+| Species | the species of the iris plant |
+
+
+## ML Techniques
+
+Tentative ML techniques:
+- [K-Nearest Neighbors](https://scikit-learn.org/stable/modules/generated/sklearn.neighbors.KNeighborsClassifier.html)
+- [Logistic Regression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html)
+- [Decision Tree](https://scikit-learn.org/stable/modules/generated/sklearn.tree.DecisionTreeClassifier.html)
+- [Random Forest](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html)
+- [Naive Bayes](https://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.GaussianNB.html)
+- [SVM](https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html)
+- [K-Means](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html)
+- [Linear Discriminant Analysis](https://scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.LinearDiscriminantAnalysis.html)
+- [Quadratic Discriminant Analysis](https://scikit-learn.org/stable/modules/generated/sklearn.discriminant_analysis.QuadraticDiscriminantAnalysis.html)
+- [Gaussian Process](https://scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcessClassifier.html)
+- [Gradient Boosting](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingClassifier.html)
+- [Bagging](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingClassifier.html)
+- [AdaBoost](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.AdaBoostClassifier.html)
+- [Extra Trees](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.ExtraTreesClassifier.html)
+- [Voting Classifier](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.VotingClassifier.html)
+- [Stacking Classifier](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.StackingClassifier.html)
+- [Bagging Classifier](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.BaggingClassifier.html)
+- [Extra Trees Classifier](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.ExtraTreesClassifier.html)
+- [Gradient Boosting Classifier](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingClassifier.html)
+- [Gaussian Process Classifier](https://scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcessClassifier.html)
+- [Random Forest Classifier](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html)
+- [Voting](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.VotingClassifier.html)
+- [Stacking](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.StackingClassifier.html)
+- [Logistic Regression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html)
+- [Perceptron](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.Perceptron.html)
+- [Passive-Aggressive](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.PassiveAggressiveClassifier.html)
+- [Ridge](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.RidgeClassifier.html)
+- [SGD](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.SGDClassifier.html)
+- [SVC](https://scikit-learn.org/stable/modules/generated/sklearn.svm.SVC.html)
+- [Linear SVC](https://scikit-learn.org/stable/modules/generated/sklearn.svm.LinearSVC.html)
+- [NuSVC](https://scikit-learn.org/stable/modules/generated/sklearn.svm.NuSVC.html)
+- [One-Class SVM](https://scikit-learn.org/stable/modules/generated/sklearn.svm.OneClassSVM.html)