About Me
Motivated Computer Science and Engineering graduate with hands-on experience in deep learning, neural networks, and data-driven projects. Proficient in implementing innovative solutions in computer vision, natural language processing, and predictive modeling. Passionate about Deep Learning and enjoy researching to contribute to the field of Computer Vision.
Education
East West University
Bachelor of Science in Computer Science and Engineering
CGPA: 3.04/4.00
Relevant Coursework: Computer Networks, Data Structures and Algorithms, Artificial Intelligence, Web Programming, Machine Learning, Digital Image Processing, Software Engineering, Statistics for Data Science.
Technical Skills
- Programming Languages: Python, Java, SQL, C++, PHP
- Machine Learning Frameworks: scikit-learn, TensorFlow, Keras, Flask, FastAPI
- Data Visualization Tools: Matplotlib, Seaborn
- Database Management: MySQL
- Tools and Platforms: Jupyter Notebook, Kaggle, Git, Google Colab, Visual Studio Code
- Area of Interest: Machine Learning, Neural Networks, Deep Learning, Computer Vision, Natural Language Processing
- Other Skills: Teamwork, Self-Learning, and Time Management
Projects
Image Caption Generators
Designed Image Captioning models using CNNs (VGG16, ResNet50, EfficientNet-B3) and LSTM on Flickr8k and Flickr30k. Evaluated the models using BLEU Scores.
Technologies: TensorFlow, Keras, NumPy, Pandas, CNNs
Image Classifications
Dog vs Cat Image Classification: Created it using both Custom CNN Model and Pre-Trained model on dogs vs cats dataset. The Custom CNN was able to achieve 80% accuracy while the Pre-Trained model MobileNetV2 achieved 98% accuracy.
Technologies: TensorFlow, Keras, CNN, Transfer Learning
Pneumonia Detection in Chest X-Rays and Explainable AI
Designed a deep learning model to classify chest X-ray images for pneumonia detection on chest x-ray dataset. Incorporated Explainable AI techniques (Grad-CAM, Lime, Integrated Gradients) to interpret the model's decisions and transparency.
Technologies: Python, TensorFlow, Keras, XAI, NumPy, EfficientNetB0
Sentiment Analysis from Text
Developed a natural language processing (NLP) model to classify emotions on ten classes in English text using LSTM.
Technologies: Python, TensorFlow, LSTM
Big Mart Sales Prediction
Developed a regression model to predict sales based on historical data.
Technologies: Python, Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn
Flickr8k Data Analysis
Conducted data analysis on Flickr8k dataset to get hidden insights.
Technologies: Python, Pandas, Matplotlib, Seaborn
Recommendation System
Build Book and Movie recommendation system using popularity based filtering, collaborative filtering and content-based approaches. Used Book-Crossing: User review ratings and MovieLens 20M Datasets.
Technologies: Python, Pandas, Numpy, Cosine Similarity
Research Publication
Explainable Artificial Intelligence for Deep Learning Based Detection of Pneumonia in Chest X-ray Images
Presented at: 3rd International Conference on Innovations in Data Analytics (ICIDA 2024)
Date: 18th-19th December 2024
Organized by: Eminent College of Management & Technology (ECMT)