Passionate about building intelligent systems that solve real-world problems
I'm a Machine Learning Engineer and Full-Stack Developer who loves the intersection of AI and software engineering. My journey spans from developing healthcare analytics models to creating production-ready AI applications that make a tangible impact.
- Advanced ML algorithms and neural architectures
- Time-series forecasting with Transformers and LSTM networks
- Production ML deployment with Docker, Kubernetes, and cloud services
- MLOps best practices and CI/CD for ML systems
- 🤖 Machine Learning & Deep Learning projects
- 📊 Data-driven dashboards and visualization tools
- 🌐 Full-stack applications with AI integration
- 📈 Time-series forecasting and predictive analytics
- 🔬 Open-source AI/ML tools
An intelligent interview preparation system powered by AI that provides real-time feedback and personalized coaching.
Features:
- 🤖 AI-powered question generation based on job roles
- 🎯 Real-time feedback on answers and body language
- 📈 Performance analytics and improvement tracking
- 💬 Natural language processing for answer evaluation
Tech Stack:PythonNLPTensorFlowFastAPIReact
An interactive web-based platform for visualizing sorting and pathfinding algorithms in real-time. Built with React and modern web technologies.
Features:
- 🔄 Real-time visualization of sorting algorithms (Bubble, Quick, Merge, Heap, Insertion)
- 🗺️ Interactive pathfinding with Dijkstra's, A*, BFS, and DFS algorithms
- 🎨 Customizable grid with obstacles and weighted nodes
- ⚡ Adjustable animation speed and array size controls
- 📊 Step-by-step algorithm execution with visual feedback
Tech Stack:ReactJavaScriptCSS3Algorithm Visualization
A comprehensive time-series forecasting system for predicting energy consumption patterns with interactive visualizations.
Features:
- 📊 Advanced time-series models (LSTM, Prophet, ARIMA)
- 📈 Interactive dashboards with Plotly/Dash
- 🔮 Multi-step ahead forecasting
- 📉 Anomaly detection and trend analysis
Tech Stack:PythonPyTorchPlotlyStreamlitPandas
Machine learning models for healthcare data analysis, providing insights for better patient outcomes and resource optimization.
Features:
- 🧠 Predictive models for patient risk assessment
- 📊 Data visualization for clinical insights
- 🔍 Feature importance analysis
- 📈 Performance metrics tracking
Tech Stack:Pythonscikit-learnPandasMatplotlib
🧠 Machine Learning
🍵 Java development
⚛️ React & Frontend
🐍 Python Development
📈 Time-Series Models
🌐 Full-Stack Dev
🤗 Hugging Face Transformers (Whisper, RoBERTa)
- 🎙️ Whisper - Worked with OpenAI's automatic speech recognition model for transcription and audio processing tasks
- 📝 RoBERTa - Implemented and fine-tuned RoBERTa models for NLP tasks including text classification and sentiment analysis
- 🤗 Hugging Face Ecosystem - Extensive experience with transformer models, tokenizers, and the Transformers library
I'm always open to interesting conversations and collaboration opportunities. Whether you want to discuss ML models, brainstorm on a project, or just chat about tech, feel free to reach out!
⚡ Fun Fact: I love blending ML + Software Engineering to build real-world solutions — from LiDAR simulations to prediction dashboards and AI interview systems!
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⭐ From atharvadk
"Building the future, one algorithm at a time"