Working at the intersection of AI, Machine Learning, and Data Analysis, with a strong focus on building practical solutions and understanding how things work under the hood.
- Hands-on AI and Machine Learning projects using real datasets
- Data analysis and visualization to extract meaningful insights
- Turning concepts into complete, usable implementations
- Deep Learning using TensorFlow and Keras
- Natural Language Processing techniques
- Transformer-based models such as DistilBERT
- Better ways to structure, train, and evaluate ML models
- AI / ML or data-focused projects
- Open-source work where learning and impact go together
- Experimental or research-driven ideas
- Improving ML pipelines and workflows
- Deploying and optimizing models
- Understanding how AI systems are built and scaled in real environments
- Python and data analysis
- Machine Learning fundamentals
- NLP and sentiment analysis
- Approaching projects from a learning-first mindset
- LinkedIn: https://www.linkedin.com/in/shaina-hussain
- Email: [email protected]
- Learns best by building, debugging, and improving projects rather than following step-by-step tutorials.
- Languages: Python, C, C++, R, JavaScript
- Libraries: Pandas, NumPy, Matplotlib, Seaborn, Plotly, Scikit-learn
- Currently learning: TensorFlow, Keras, NLP, Transformers (DistilBERT)
- Tools: Git, GitHub, Streamlit, Power BI (basics), PyCharm, VS Code
- AI and Machine Learning implementations
- Data analysis and visualization work
- Python-based experiments and utilities
Each repository is maintained with clarity and clear intent.