My Work
Explore my portfolio of AI, Machine Learning, and Data Science projects, crafted with cutting-edge technologies.
I've built AI-driven solutions, predictive models, and data science applications across multiple domains. Here are some of my research and development highlights:
ASD Detection System
Developed an advanced autism detection system leveraging deep learning and AI-driven analysis of facial expressions and speech patterns. Achieved 87% accuracy in early diagnosis prediction using a custom CNN-LSTM architecture.
Tech Stack: TensorFlow, OpenCV, PyTorch, Flask, React.js
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Breast Cancer Prediction
Developed a predictive analytics model for breast cancer diagnosis using clinical data. Implemented advanced feature selection, hyperparameter tuning, and ensemble learning techniques, achieving 94% accuracy on test data.
Tech Stack: Scikit-Learn, NumPy, Pandas, XGBoost, Flask API
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Cat-Dog-Panda Classification & Object Detection
Built a deep learning pipeline for multi-class image classification and real-time object detection using YOLOv8. Integrated with PyTorch-based ResNet-18 for enhanced accuracy and deployed as a web service.
Tech Stack: YOLOv8, PyTorch, OpenCV, Scikit-Learn, Label Studio
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Sowing Success: Crop Selection with ML
Designed an intelligent system for crop selection based on soil metrics and environmental factors. Used Random Forest and XGBoost for multi-class classification with 92% accuracy and feature importance analysis.
Tech Stack: Scikit-learn, Pandas, NumPy, Random Forest, XGBoost
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Customer Churn Prediction
Developed a machine learning model for predicting customer churn in a telecom company. Implemented logistic regression, decision trees, and neural networks with SMOTE for handling class imbalance, improving retention by 24%.
Tech Stack: Scikit-learn, Pandas, NumPy, Matplotlib, TensorFlow
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Automated Data Extraction System
Engineered a high-speed web scraper with NLP capabilities for structured data extraction from various sources. Implemented named entity recognition and text classification for automated data categorization.
Tech Stack: Scrapy, Selenium, NLTK, spaCy, Hugging Face Transformers
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Time Series Forecasting for Stock Prices
Created a time series forecasting system for stock price prediction using LSTM networks and traditional statistical methods. Incorporated sentiment analysis from financial news for improved accuracy.
Tech Stack: TensorFlow, ARIMA, Prophet, LSTM, NLP
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Recommendation Engine
Built a hybrid recommendation system combining collaborative filtering and content-based approaches. Implemented matrix factorization and deep learning techniques to provide personalized recommendations.
Tech Stack: PyTorch, Surprise, LightFM, FastAPI
View ProjectHave a Data Science Project in Mind?
I'm always open to discussing new AI, ML, and data science research opportunities. Let's collaborate and transform your data into actionable insights!