I am a Master's student in Computer Science with hands-on experience in Machine Learning, Computer Vision, Data Engineering, Backend Development, and AI-powered applications.
I enjoy building practical AI and software projects that solve real-world problems using Python, PyTorch, scikit-learn, React, FastAPI, SQL, Docker, and cloud tools.
- 🎓 Master's student in Computer Science
- 💻 Interested in AI/ML, Data Engineering, Backend Development, and Computer Vision
- 🧠 Building projects in Explainable AI, Intrusion Detection, RAG, Object Detection, and Data Pipelines
- 🔍 Actively looking for Software Engineering, AI/ML, Data Engineering, and Research opportunities
- 📍 Based in Jacksonville, Florida
Programming Languages:
Python, Java, JavaScript, SQL, C++, HTML, CSS
AI/ML & Data Science:
PyTorch, scikit-learn, OpenCV, NumPy, Pandas, Matplotlib, CNNs, Anomaly Detection, Explainable AI, Grad-CAM, Integrated Gradients
Backend & Web Development:
FastAPI, REST APIs, React, Vite, Node.js, HTML/CSS, API Integration
Databases & Data Engineering:
PostgreSQL, MySQL, MongoDB, ETL Pipelines, Web Scraping, Data Cleaning, Data Aggregation
Tools & Platforms:
Git, GitHub, Docker, AWS, Linux, VS Code, Jupyter Notebook, Postman
Built a CNN-based medical image classification system using the PathMNIST dataset and applied Grad-CAM and Integrated Gradients to understand model predictions.
Tech Stack: Python, PyTorch, MedMNIST, OpenCV, NumPy, Matplotlib
Key Work: CNN training, model evaluation, confusion matrix analysis, explainability visualizations, confidence-drop testing
Developed an anomaly detection-based IDS system to identify unseen cyberattacks using the NSL-KDD dataset.
Tech Stack: Python, scikit-learn, Pandas, NumPy, Matplotlib
Key Work: Isolation Forest, One-Class SVM, held-out attack testing, precision/recall/F1 evaluation
Created a real-time object detection dashboard that connects a Python AI backend with a Unity interface for AR-style visualization.
Tech Stack: Python, Unity, YOLO/MobileNet, REST API/WebSocket
Key Work: real-time detection, bounding box data transfer, dashboard visualization, desktop AR prototype
Built an automated pipeline to collect, clean, enrich, and score data from multiple public sources and APIs.
Tech Stack: Python, BeautifulSoup, Selenium, Pandas, PostgreSQL, APIs
Key Work: web scraping, API enrichment, data normalization, lead scoring, automated reporting
Worked on improving reflective object segmentation using SAM-2 with depth-guided prompting and evaluation metrics.
Tech Stack: Python, PyTorch, SAM-2, OpenCV, MiDaS/Depth Estimation
Key Work: segmentation evaluation, IoU/Dice metrics, qualitative overlays, depth-based prompt tuning
I am currently improving my skills in:
- Advanced Machine Learning and Deep Learning
- RAG and LLM-based applications
- Backend API development
- Cloud deployment and Docker
- Production-ready AI project development
- GitHub: https://github.com/deepakreddyyadama
- LinkedIn: https://www.linkedin.com/in/deepak-reddy-7a5944250/
- Portfolio: https://deepak-portfolio-flax.vercel.app/
- Email: deepakreddyyadama@gmail.com
My goal is to build strong, real-world software and AI projects that demonstrate practical problem-solving, clean engineering, and continuous learning.# Hi, I'm Deepak Reddy Yadama 👋
I am a Master's student in Computer Science with hands-on experience in Machine Learning, Computer Vision, Data Engineering, Backend Development, and AI-powered applications.
I enjoy building practical AI and software projects that solve real-world problems using Python, PyTorch, scikit-learn, React, FastAPI, SQL, Docker, and cloud tools.