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-detecting-fake-news-using-tf-idf-vectorizer-and-passive-aggressive-classifier

breast-cancer-prediction-using-adaboost

car-price

decision-tree-to-predict-income

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 cross-validation.

deeplearning

dviz-course

Data visualization course material

email-spam-classifer-with-svm-linear-nonlinear

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 classifier to classify emails and compare the performance with the linear SVM model.

letter-recognition-using-svm

Letter Recognition using non linear rbf kernel in SVM

logisticregression-telecom-churn

matplotlib

mlprojects

multiple-linear-regression

nlp

personalized-medicine-redefining-cancer-treatment

ridge-and-lasso-regression

simple-linear-regression-to-predict-sales-on-tv-marketing-budget

sms-classifier-using-bernoulli-naive-bayes

Classification of message whether spam or not using Multinomial Naive Bayes Classification

talkingdata-adtracking-fraud-detection-challenge

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

text-summarizer

video_classifications