| { | |
| "heading": "Machine Learning", | |
| "intro": "My machine learning expertise spans from traditional algorithms to deep learning systems that solve real business challenges. I've built end-to-end ML pipelines that deliver measurable impact, combining the right models with appropriate feature engineering techniques. I focus on creating solutions that are not only technically sound but also deployable, maintainable, and integrated with business workflows. With a solid foundation in Python-based ML frameworks and cloud deployment platforms, I develop models that generate actionable predictions and insights.", | |
| "skills": [ | |
| { | |
| "category": "Frameworks & Libraries", | |
| "items": ["TensorFlow/Keras", "PyTorch", "Scikit-Learn", "XGBoost/LightGBM"] | |
| }, | |
| { | |
| "category": "ML Techniques", | |
| "items": ["Supervised Learning", "Unsupervised Learning", "Deep Learning", "Natural Language Processing"] | |
| }, | |
| { | |
| "category": "MLOps", | |
| "items": ["ML Pipelines", "Model Monitoring", "Deployment Strategies", "Version Control (DVC)"] | |
| }, | |
| { | |
| "category": "Cloud ML Services", | |
| "items": ["AWS SageMaker", "Google AI Platform", "Azure ML", "MLflow"] | |
| } | |
| ], | |
| "projects": [ | |
| { | |
| "title": "University Admission Predictor", | |
| "url": "#", | |
| "description": "Built a regression model to predict the chances of a student getting admitted to top universities based on academic profiles. The project includes feature importance analysis, model tuning, and a live demo deployed with Streamlit.", | |
| "tech_stack": "Scikit-learn, Streamlit, NumPy" | |
| }, | |
| { | |
| "title": "AI Chat Assistant for Recruiters", | |
| "url": "https://huggingface.co/spaces/Manyue-DataScientist/AI-Assistant", | |
| "description": "A custom-trained assistant that answers queries about my resume and portfolio using NLP and retrieval techniques. Built to simulate real-time interactions with hiring teams, this project showcases my ability to work with large language models and create practical AI applications.", | |
| "tech_stack": "LangChain, OpenAI, Gradio" | |
| }, | |
| { | |
| "title": "Speaker Diarization Application", | |
| "url": "https://huggingface.co/spaces/Manyue-DataScientist/speaker-diarization-app-v2", | |
| "description": "Developed an advanced multi-speaker audio processing system that performs speaker diarization, transcription, and summarization to extract meaningful insights from multi-speaker conversations.", | |
| "tech_stack": "PyTorch, Hugging Face Transformers, Gradio" | |
| } | |
| ] | |
| } |