Posts by Pranjal (14)

Pranjal 2026-01-01

Earthquake and Rainfall Prediction

Summary The design aims to dissect data handed by seismic sensors and downfall sensors to develop a model that prognosticates the circumstance and intensity of earthquakes, frequency and circumstance of downfall. Voice based completely intelligent assistants require an activating phrase, also known as a wake - word, before the order may be digital. It can be integrated with online net services to gather statistics needed for tool and help the user manage their responsibilities. The majority of voice assistants that are now available aren`t flowless. Using web browser Libraries 1. Pyttsx 2. Speech Recognition 3. Whatkit Library 4. Wikipedia Tech Stack: Python, AI-ML Based classification algorithms

Pranjal 2026-01-01

Real-Time Stock Watchlist Application

Summary 1. Developed a full-stack application with Flutter(frontend) and TypeScript/Express (backend) using PostgreSQL. 2. This involved creating RESTful APIs, optimizing user interfaces, and containerizing the backend with Docker, aligning with the role’s backend and frontend requirements. Note 1.The frontend of the Real-Time Stock Watchlist Management Web Application is built using Flutter and Dart, providing a responsive user interface for adding, viewing, and managing stocks. The frontend communicates with the backend via REST API calls to display real-time stock information. 2. The backend, developed using TypeScript and Express, handles the API logic, managing stock-related data and processing user requests. 3. It interfaces with a PostgreSQL database to store and retrieve stock details and portfolio information. Both the backend and database are containerized using Docker, ensuring that the application runs in isolated, consistent environments. 4. The frontend container hosts the Flutter application, while the backend container runs the Express server. 5. The database container holds the PostgreSQL instance, allowing seamless integration between the backend and the database for CRUD operations on stock data. This containerized architecture ensures modularity and simplifies deployment and scaling. Tech Stack: Flutter, Node.js, TypeScript/Express, Docker

Pranjal 2026-01-01

Fake News Classifier

Summary 1. Fake news can be very harmful and can affect people’s daily life and have adverse effects on it. 2. Social media has become a daily part of people’s lives and is a major source for spreading of rumors and news which can be fake. Fake News Classification using NLP 1. Setup: Importing Libraries 2. Loading the data set and exploratory Data Analysis 3. Text - Pre Processing 4. Extraction of vectors from text( TF-IDF Vectorization) 5. Running ML Classification Algorithms 6. Generating classification reports and classification matrix 3 -> Tokenization, Stemming, Stop-word Removal 4 -> Logistic Regression, Criterion Boost, Random Forest Real Chart 1. Data Collection 2. Text Processing 3. TF-IDF vectorization 4. Training - Validation 5. Classification Report and Confusion Matrix Tech Stack: Python, AI-ML Based classification algorithms

Pranjal 2026-01-01

Desktop Voice Assistant

Summary • Interesting Feature: Voice based completely intelligent assistants require an activating phrase, also known as a wake - word, before the order may be digital. Tech Stack: Python, Speech Recognition based techniques

Pranjal 2026-01-01

IOT solutions for SME sector

Description: 1. Project is a sustainability-focused data platform that tracks and logs sustainability related metrics such as energy consumption and carbon emissions. 2. It uses Python and SQLite as the backend for data management, while frontend is built with HTML5 and CSS3 for clean user interaction. 3. Application is containerized using Docker and hosted on AWS for reliability. Tech Stack: HTML5, CSS3, Python, DB SQLite, Docker and AWS

1 2 3