Sweety Biswas

Utilized SQL and Python to extract,clean and analyze large datasets. Well versed in backend automation, webapi automation and ui automation. Technology used: Python,SQL,Flask, Selenium, Jenkins, Github

Diabetes Prediction using machine learning. Predicting that whether patient has diabetes or not on the basis of some features.Perform Exploratory data analysis, Data Preprocessing, Feature Engineering, Feature Scaling, Data visualization, Model Building using Various Supervised Machine learning algorithms - K-Nearest Neighbor (KNN), Logistic Regression (LR), Decision Tree (DT), Support Vector Machine (SVM), Naive-Bayes Classifier, Random Forest.

Awarded Letter of Recommendation for exceptional performance during the internship period. AI Product/Service Prototype Reports. Market Segmentation using Machine Learning and Data Analysis. Analyzing of Tourism Market in India for a Travel Hostel Startup Perform Exploratory data analysis, Data Preprocessing, Data Cleaning,Feature Engineering, Feature Scaling, Data visualization, Model Building using Unsupervised Machine learning algorithms – Hierarchical Clustering,K-means Clustering

Awarded Letter of Recommendation for exceptional performance during the internship period. Iris Flowers Classification. Prediction using Decision Tree Algorithm on Iris dataset. Exploratory Data Analysis on Terrorism Dataset , trying to find out the hot zone of terrorism. ETL on Amazon dataset and find sales-trend -> Monthwise, Yearwise, Yearly Monthwise. Predict the percentage of an student based on the number of study hours.