const shalini = {
pronouns: "she" | "her",
location: "India 🇮🇳",
code: ["Python", "R", "SQL"],
askMeAbout: ["ML", "Deep Learning", "Data Viz", "AI Ethics"],
technologies: {
ml: ["TensorFlow", "PyTorch", "Scikit-learn", "Keras"],
dataStack: ["Pandas", "NumPy", "Matplotlib", "Seaborn", "Plotly"],
cloudTools: ["AWS", "Docker", "Git"],
databases: ["MySQL", "PostgreSQL", "MongoDB"]
},
currentVibes: "Building models that predict the unpredictable 🎯",
funFact: "I debug with print statements and I'm not ashamed 😄"
};|
Data Science Uncovering insights from complex datasets |
Machine Learning Building predictive models that learn |
Deep Learning Crafting neural networks that think |
Regression | Time Series Analysis
Predicting bike rental patterns to optimize fleet distribution. Engineered features from temporal and weather data, achieving 85%+ accuracy in demand forecasting.
Python Pandas Scikit-learn Matplotlib Seaborn Feature Engineering
Computer Vision | CNN | Medical AI
Early detection of skin cancer using deep learning. Built CNN architecture with data augmentation and handled class imbalance for better accuracy.
TensorFlow Keras OpenCV CNN Transfer Learning Medical Imaging
Advanced Regression | Ridge & Lasso
Predicting real estate prices with 90%+ R² score. Extensive EDA, feature engineering, and regularization techniques for robust predictions.
Python Scikit-learn Ridge Regression Lasso Cross-Validation
EDA | Data Visualization | Analytics
Understanding what makes content go viral. Analyzed trending video patterns and created interactive visualizations to identify engagement drivers.
Python Pandas Seaborn Plotly WordCloud Statistical Analysis
🔍 View All Projects
| Project | Description | Tech Stack | Link |
|---|---|---|---|
| 🚴♀️ Bike Sharing | Demand forecasting with 85%+ accuracy | Python, ML, Time Series | View |
| 🔬 Melanoma Detection | CNN-based skin cancer detection | TensorFlow, Keras, CV | View |
| 🏘️ House Pricing | Real estate price prediction (R²>90%) | Scikit-learn, Regression | View |
| 📹 YouTube Analysis | Viral content pattern analysis | EDA, Visualization | View |
current_status:
- role: "Data Science Explorer 🚀"
- learning: ["MLOps", "Transformer Models", "Cloud Deployment", "LLMs"]
- reading: "Designing Machine Learning Systems by Chip Huyen"
- working_on: "End-to-end ML pipeline automation"
mission_2025:
technical:
- "Deploy 5 ML models to production ☁️"
- "Master Kubernetes for ML workflows 🐳"
- "Build an end-to-end recommendation system 🎯"
- "Contribute to HuggingFace Transformers 🤗"
- "Implement MLOps best practices 🔄"
creative:
- "Start a ML blog series 📝"
- "Create interactive data viz dashboards 📊"
- "Build AI tools for social good 🌍"
- "Kaggle Expert rank (fingers crossed! 🤞)"
- "YouTube tutorials on ML concepts 🎥"
community:
- "Mentor 10+ aspiring data scientists 👥"
- "Speak at local tech meetups 🎤"
- "Open source contributions every week 💻"
- "Build in public, share learnings 📢"
- "Organize ML study groups 📚"
side_quests:
- "Building a cricket score predictor 🏏"
- "Creating a mood-based playlist generator 🎵"
- "Automating my daily workflows ⚙️"
- "Personal portfolio website with Next.js 🌐"If you like my projects and want to support my work, you can:
Or simply:
- ⭐ Star my repositories
- 🍴 Fork and contribute
- 📢 Share with others
- 💬 Provide feedback
| 🐛 First Bug Was an actual moth in 1947! |
📊 Data Generated 2.5 quintillion bytes daily |
🤖 AI Term Coined in 1956 at Dartmouth |
🧠 Neural Networks Inspired by human brain |
"Data is the new oil, but like oil, it's valuable only when refined and analyzed properly."
My Approach:
- 🎯 Focus on solving real-world problems
- 📚 Never stop learning and experimenting
- 🤝 Collaborate and share knowledge
- ⚡ Write clean, maintainable code
- 🌱 Contribute to open source
- 💪 Embrace failures as learning opportunities
Last Updated: October 2025 | Made with ❤️ and lots of ☕