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๐ฑ Iโm currently learning Neural Network
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๐ฏ Iโm looking to collaborate on real world projects
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๐ฌ Ask me about Python, MongoDB, MySQL
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๐ซ How to reach me dharmaprakash144@gmail.com
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Real-time AI system for autonomous vehicle safety
- Algorithm: Isolation Forest for unsupervised anomaly detection
- Dataset: Vehicle telemetry data (speed, acceleration, GPS, sensor readings)
- Impact: Detects unsafe driving patterns with 94% accuracy
- Tech Stack: Python, scikit-learn, Streamlit, pandas, matplotlib
- Features: Real-time monitoring, interactive dashboard, alert system
IoT + AI solution for agricultural threat detection
- Hardware: Arduino, thermal sensors, ultrasonic sensors, Wi-Fi modules
- AI Component: Pattern recognition for animal threat classification
- Achievement: 2nd Place at Pitch Perfect '24 Hackathon
- Impact: Automated detection and response to wildlife threats
Comprehensive collection of ML implementations
- Algorithms: Linear/Logistic Regression, Decision Trees, Random Forest, SVM
- Projects: Data preprocessing, feature engineering, model optimization
- Tools: Jupyter Notebooks, Google Colab, scikit-learn, pandas
| Category | Technologies | Experience Level |
|---|---|---|
| Machine Learning | scikit-learn, pandas, numpy | ๐ข๐ข๐ข๐กโช Advanced |
| Deep Learning | TensorFlow, PyTorch, Keras | ๐ข๐ข๐กโชโช Intermediate |
| Data Analysis | pandas, matplotlib, seaborn | ๐ข๐ข๐ข๐ขโช Proficient |
| IoT Development | Arduino, Raspberry Pi, Sensors | ๐ข๐ข๐ขโชโช Intermediate |
| Web Development | Streamlit, HTML/CSS/JS | ๐ข๐ข๐ขโชโช Intermediate |
%%{init: {'theme':'dark'}}%%
graph LR
A[๐ง Neural Networks] --> B[๐ฌ Deep Learning]
B --> C[๐๏ธ Computer Vision]
C --> D[๐ค Advanced AI Systems]
D --> E[๐ AI in Production]
style A fill:#ff6b6b
style B fill:#4ecdc4
style C fill:#45b7d1
style D fill:#96ceb4
style E fill:#feca57
- Phase 1: Mastering Neural Network architectures (Current)
- Phase 2: Advanced Deep Learning frameworks
- Phase 3: Computer Vision and Image Processing
- Phase 4: Production-ready AI systems
- Phase 5: MLOps and AI deployment strategies
| Achievement | Details | Year |
|---|---|---|
| ๐ฅ Hackathon Winner | Pitch Perfect '24 - Animal Threat Detection | 2024 |
| ๐ Python Intern | CodSoft - ML Projects & Algorithms | 2024 |
| ๐ Certifications | Python, NPTEL, Git & GitHub | 2024 |
| ๐ค AI Project Lead | SDV Anomaly Detection System | 2025 |
| ๐ Research Focus | Machine Learning in Autonomous Systems | 2025 |
- ๐ Autonomous Vehicle Safety: Developing AI systems for real-time anomaly detection in self-driving cars
- ๐ฑ Smart Agriculture: IoT + AI solutions for sustainable farming and crop protection
- ๐ Anomaly Detection: Unsupervised learning for identifying unusual patterns in complex datasets
- ๐ Edge AI: Deploying machine learning models on IoT devices and embedded systems
- ๐ MLOps: Best practices for deploying and maintaining AI systems in production
- Complete Neural Networks specialization
- Publish research paper on SDV anomaly detection
- Contribute to open-source ML projects
- Build production-ready AI applications
- Expand IoT + AI integration expertise
- โ Implemented Isolation Forest for SDV anomaly detection
- โ Won 2nd place in hackathon with IoT solution
- โ Completed Python programming internship
- โ Built interactive ML dashboard with Streamlit
- โ Integrated hardware sensors with AI algorithms
I'm always excited to collaborate on:
- ๐ค AI/ML research projects
- ๐ Autonomous vehicle technology
- ๐ฑ Smart IoT solutions
- ๐ Data science challenges
- ๐ฌ Open-source contributions
Looking for opportunities in:
- Machine Learning Engineering roles
- AI Research internships
- IoT + AI project collaborations
- Hackathons and competitions
๐ก "Building the future with AI, one algorithm at a time" ๐ก
"Passionate about turning complex problems into intelligent solutions"