Dharti Patel

• Face Match Application - Facial Recognition with Live Video Feed Fetching, – Developing a facial recognition application to process the video feed in real-time fetching from a database
• Recognizing and obtaining the facial features by getting coordinates of various organs on the face
• Storing the key features of the face into a repository instead of storing the images in order to eliminate any perceptible time delay between ingest and query, which plays a crucial role in time-critical situations
• Detecting the facial expression of the person and tracking the faces across different video frames
• Term Paper - Accuracy of Probabilistic and Deterministic Record Linkage December 2022
• Business Analytics Term Project - Machine Learning using Spam Dataset

• Analyzed the Spam dataset using KNN, Random Forest, Logistic Regression, AdaBoost, and Ensemble al- gorithms to characterize good and fake emails
• Data, – Trained, tested, and analyzed the accuracy of various Machine Learning algorithms
• Performed descriptive statistics, data cleaning and dimension reduction, and data visualization
• Data Visualization - Team Tesla: Depicting Sales of Electric Vehicles

• Found the vehicles that had the fastest acceleration using an online database in R Studio
• Diabetes Prediction Using Machine Learning Methods, Fostered innovation by helping students with engineering graphics design by using drafter and CAD soft- wares
• Promoted collaboration by holding office hours and resolving the doubts of students.

• Implemented a diabetes prediction model using machine learning methods using different algorithms such as support vector machine (SVM), decision tree, logistic regression, and random forest
• Analyzed the performance of different methods
• Optimizers in Deep Learning, Implemented various optimizers such as Gradient Decent, Stochastic Gradient Decent, SGD+, Momentum
• RMSProp, Adagrad, and Adam
• Created an MNIST Dataset (handwritten number database)
• Trained and tested the accuracy and loss of different optimizers
• Wine Quality prediction March 2023 – Analyze Wine Dataset using KNN,LogisticRegression, KNN,DecisonTree,RandomForest and Ensemble Learn- ing
• Trained and tested the accuracy and precision score of different algorithms.

• Developed digital databases to keep a record of purchases and sales
• Gained valuable information about the higher-selling parts by analyzing the data
• Created user-friendly UI/UX applications using Python, HTML5, and PHP
• Developed and hosted websites for college technical festivals (Tech fests).

• Created a database management system using a combination of programming languages like HTML, CSS
• Python, and PHP to implement and track the placement record of the students
• Helped alleviate the maintenance of the hand-written and manual data by digitizing it to track the placement record of students efficiently
• Hosted and uploaded the database to an online database server to provide easy access to the students, faculties, or other authorities
• Roads to Success

• Assisted kids to help them learn summer activities and taught them different sports games and other co- curricular activities
• Inspired and empowered young people for their future and took them on a one-day outing.

GPA: 3.80 / 4.00

• Graduate Scholar Award Scholarship Recipient
• Relevant Coursework: Python & Machine Learning
• Roads To Success(NGO) Member

• GPA: 8.97/10