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Spam SMS Detection Project implemented using NLP & Transformers. DistilBERT - a hugging face Transformer model for text classification is used to fine-tune to best suit data to achieve the best results. Multinomial Naive Bayes achieved an F1 score of 0.94, the model was deployed on the Flask server. Application deployed in Google Cloud Platform
The aim is to develop an ML- based predictive classification model (logistic regression & decision trees) to predict which hotel booking is likely to be canceled. This is done by analysing different attributes of customer's booking details. Being able to predict accurately in advance if a booking is likely to be canceled will help formulate prof…
This is a Bio Informatics project for the classification of types of Leukemia Cancer i.e., ALL & AML based on gene expression data. An accuracy of 0.94 has been achieved by using Support Vector Machine(SVM). The dataset has been collected from 'Kaggle' where gene descriptions are given as the features.
This project involves predicting customer churn in a telecommunications company using machine learning techniques, exploring various features' impact, optimizing models, and identifying key factors influencing churn.
The goal is to eliminate manual work in identifying faulty wafers. Opening and handling suspected wafers disrupts the entire process. False negatives result in wasted time, manpower, and costs.
This project demonstrates building a classification model for imbalanced data. Feature engineering, feature selection and extensive EDA. Comparing of logistic regression, random forest and ADA Boost models are done before finalizing the best model.
In this project, we have worked with hundreds of anonymized features to predict if a customer is satisfied or dissatisfied with their banking experience.
Time Series Classification Part 2 Binary and Multiclass Classification. An interesting task in machine learning is classification of time series. In this problem, we will classify the activities of humans based on time series obtained by a Wireless Sensor Network.
Developed Machine Learning Model to categorize customer with more than 91% accuracy and 88% roc_auc score. Best ML model is selected after evaluating all performance metric like Accuracy, Precision & recall
This is a project demonstrating Logistic Regression method using Python. An education company named X Education sells online courses to industry professionals. On any given day, many professionals who are interested in the courses land on their website and browse for courses.