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1. TalkingData-AdTracking-Fraud-Detection-Challenge TalkingData-AdTracking-Fraud-Detection-Challenge Public

   This project in the domain of 'digital fraud'. Exploring the data. Feature Engineering. Model Building and Evaluation using Boosting Techniques (AdaBoost, Gradient Boost, XGBoost)

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2. Personalized-Medicine-Redefining-Cancer-Treatment Personalized-Medicine-Redefining-Cancer-Treatment Public

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3. Decision-Tree-to-predict-Income Decision-Tree-to-predict-Income Public

   Clean and prepare the data, build a decision tree with default hyperparameters, understand all the hyperparameters that we can tune, and finally choose the optimal hyperparameters using grid search…

   Jupyter Notebook

4. Email-spam-classifer-with-SVM-Linear-NonLinear Email-spam-classifer-with-SVM-Linear-NonLinear Public

   Build a linear SVM classifier to classify emails into spam and ham. The dataset, taken from the UCI ML repository, contains about 4600 emails labelled as spam or ham. Build a non-linear SVM classif…

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5. Breast-cancer-Prediction-using-AdaBoost Breast-cancer-Prediction-using-AdaBoost Public

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6. Letter-Recognition-using-SVM Letter-Recognition-using-SVM Public

   Letter Recognition using non linear rbf kernel in SVM

   Jupyter Notebook 1