Projects
Twitter-Sentimental Analysis| Hate and Abusive content classification
Developed a robust machine learning model for sentiment analysis and hate speech detection on Twitter data. Utilized natural language processing (NLP) techniques to preprocess and analyze text data
TOOLS REQUIRED: NLTK, re, matplotlib ,Logistic Regression, tfidfvectorizer , SVM
DURING: 2nd year 2nd Semister
E-Learning Website
This provides trainers, learners, and others involved in education with information, tools, and resources to support and enhance education delivery and management.
TOOLS REQUIRED: HTML, CSS, JavaScript
DURATION: 2nd year 1st Semister
BANK DATA DEPOSIT PREDICTION
In this Bank Data Deposit prediction. I used Machine Learning Algorithms and Trained my model with some data. And It helped me to predict whether the customer will Deposit in the particular Bank or not.
MODULES REQUIRED: Supervised Algorithms, Pandas, Matplotlib, seaborn(For Visualization) .
DURATION: 3rd year 1st Semister
ATTENDANCE MANAGEMENT USING FACE RECOGNITION PYTHON PROJECT
In this Attendance management system using python .The webcam recognizes the face of the Student and stores the time and name of the student in an Excel sheet. In this way we can use face recognition and take attendance of the student.
TOOLS REQUIRED: Python, SVM, Face-Recognition Module (Deep Learning)
DURATION: 3rd year 1st Semister
2015-2019 MN CRASH FACTS DASHBOARD USING TABLEAU
The project aims to create an interactive dashboard using Tableau to visualize crash data from Minnesota spanning the years 2015 to 2019. The dashboard will provide insights into various aspects of road accidents such as the frequency of crashes, contributing factors, types of vehicles involved, and geographical distribution of accidents across Minnesota.
TOOLS REQUIRED: Tableau
DURATION: 3rd year 2nd Semister
AN AUTOMATED RESUME SCREENING SYSTEM USING NATURAL LANGUAGE PROCESSING AND SIMILARITY
Conventionally, resume screening has been a manual process, with hiring managers spending significant time reviewing each resume individually. Besides the fact that it is a time-consuming procedure, there are also unknown biases. Therefore, this is a method for automating resume screening using Artificial Intelligence and Machine Learning
TOOLS REQUIRED: Python, Deep Learning Modules ,NLTK, Matplotlib
DURATION: 4th year 1st semister