GitHub - 272006Sakshi/Machine-Learning-Projects: A collection of essential machine learning algorithms implemented from scratch and with libraries. Ideal for students and beginners to understand core ML concepts through hands-on examples.

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Name		Name	Last commit message	Last commit date
Latest commit History 24 Commits
DecisionTree.ipynb		DecisionTree.ipynb
DecisionTreeExercise.ipynb		DecisionTreeExercise.ipynb
EDA.ipynb		EDA.ipynb
EmailSpam.ipynb		EmailSpam.ipynb
GD.ipynb		GD.ipynb
KNN.ipynb		KNN.ipynb
KmeansClustering.ipynb		KmeansClustering.ipynb
L1&L2Regularization.ipynb		L1&L2Regularization.ipynb
LogisticRegression.ipynb		LogisticRegression.ipynb
NaiveBayes.ipynb		NaiveBayes.ipynb
OneHotEncoder.ipynb		OneHotEncoder.ipynb
OneHotEncoding.ipynb		OneHotEncoding.ipynb
README.md		README.md
ROCcurve.ipynb		ROCcurve.ipynb
RidgeRegression(L2)_2D&nD.ipynb		RidgeRegression(L2)_2D&nD.ipynb
SimpleLinRegression.ipynb		SimpleLinRegression.ipynb
TrainTest.ipynb		TrainTest.ipynb
batch_GD.ipynb		batch_GD.ipynb
multipleLinRegression.ipynb		multipleLinRegression.ipynb

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A collection of essential machine learning algorithms implemented from scratch and with libraries. Ideal for students and beginners to understand core ML concepts through hands-on examples.

batchgd decisiontree eda gradientdecrent kmeansclustering knn l1l2regularization labelencoder linrarregression logisticregression nivebayes onehotencoder outlierdetection sochasticgd svm