🎓 M.Tech – Smart Electric Grid (EEE) | NIT Warangal
🤖 Machine Learning & AI Enthusiast
🛠️ ML Engineer in progress | System-oriented learner

I build end-to-end Machine Learning solutions — from data analysis and model training to API development and lightweight deployment. I focus on practical, real-world applications rather than isolated experiments.

• 📊 Exploring real-world datasets (Kaggle & open datasets)
• 🤖 Building ML & basic DL models
• 🧠 NLP experiments (text classification, preprocessing, embeddings)
• 🌐 Creating ML APIs using FastAPI
• 🐳 Containerizing ML projects with Docker
• 📈 Building interactive ML apps using Streamlit
• 🔜 Gradually moving toward LLMs, RAG, and applied AI systems

• Python
• SQL
• Git & GitHub
• Jupyter Notebook, Google Colab
• VS Code

• NumPy
• Pandas
• Scikit-learn
• TensorFlow
• Natural Language Processing (tokenization, vectorization, embeddings)

• Matplotlib
• Seaborn
• Streamlit

• FastAPI
• Docker (containerized ML services)
• REST APIs for ML inference

• Supervised & Unsupervised Learning
• Feature Engineering
• Model Evaluation (Accuracy, Precision, Recall, F1-score, ROC-AUC)
• Overfitting & Regularization
• Bias–Variance Tradeoff

• End-to-End ML Projects

  • Data preprocessing → model training → evaluation
  • Served models using FastAPI

• NLP Projects

  • Text classification & preprocessing pipelines
  • Feature extraction using traditional NLP techniques

• Interactive ML Apps

  • Streamlit dashboards for model inference and visualization

• Containerized ML Systems

  • Dockerized ML applications for reproducibility

Each project includes a clear problem statement, approach, and results.

I’m open to collaborating on:

• End-to-end ML systems
• NLP applications
• FastAPI-based ML services
• Streamlit dashboards for ML

If you like building real things, feel free to connect.