Innovative Solutions
Creating impactful applications that enhance user experiences and efficiency.
AI/ML & Data Engineering Expertise
AI & Machine Learning:
Deep Learning: Expertise in CNN, RCNN, and transfer learning for tasks like facial emotion detection.
Data Processing: Preprocessing, feature engineering, and model optimization using Python, TensorFlow, and Keras.
Computer Vision: OpenCV-based image processing and real-time detection models
MERN Stack
I specialize in building scalable and high-performance web applications using the MERN stack (MongoDB, Express.js, React.js, Node.js).
🔹 Frontend: React.js with Tailwind CSS for a dynamic and responsive UI.
🔹 Backend: Node.js & Express.js for efficient server-side logic.
🔹 Database: MongoDB for flexible and scalable data management.
🔹 API Development: RESTful APIs for seamless client-server communication.
🔹 Authentication & Security: JWT authentication and bcrypt for secure user authentication.
My Work
startup- GharKiBai
GlobalTech Pvt. Ltd.
Info Origin inc
At Info Origin Technologies, I worked on data engineering, analytics, and web development, optimizing large-scale data processing and enhancing business insights.
Key Contributions:
🔹 Built Scalable Data Pipelines – Designed and developed efficient ETL workflows for large datasets.
🔹 Optimized Data Processing – Automated and streamlined Excel-based data workflows for better decision-making.
🔹 Data Visualization – Created insightful dashboards using Python (Matplotlib, Pandas) for strategic business analysis.
Stock Market Prediction Using LSTM
Data Collection & Preprocessing
Fetched historical stock price data from Yahoo Finance or Alpha Vantage API.
Applied MinMax Scaling to normalize data for better LSTM performance.
🔹 LSTM Model Implementation
Designed an LSTM-based neural network using TensorFlow/Keras.
Optimized hyperparameters like the number of layers, neurons, batch size, and learning rate.
Implemented dropout layers to prevent overfitting.
🔹 Training & Evaluation
Used Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) to evaluate prediction accuracy.
Compared LSTM predictions with actual stock prices using Matplotlib and Plotly for visualization.
Fine-tuned the model with Adam optimizer and ReLU activation for better accuracy.
