Building AI Systems • Exploring LLMs • Learning by Building
- 🎓 Undergraduate Student
- 🤖 Passionate about Artificial Intelligence and Machine Learning
- 🧠 Exploring LLMs, SLMs, Alignment, Interpretability, and AI Safety
- 🔬 Interested in how neural networks think and reason
- 🛠 Building practical AI systems from training to deployment
- 📚 Learning AI from first principles
LLMs & Transformers
├── Fine-Tuning
├── Alignment
├── Evaluation
├── Interpretability
└── Agent Systems
Machine Learning
├── Deep Learning
├── NLP
├── Computer Vision
└── MLOps
Systems
├── Python
├── APIs
├── Databases
└── Cloud Deployment
AI-powered verification and fact-checking pipeline.
Focus Areas
- Claim Extraction
- Evidence Retrieval
- Contradiction Detection
- Confidence Scoring
- Explainable Verification
Open-source framework for auditing AI systems.
Features
- Model Evaluation
- Bias Analysis
- Safety Checks
- Performance Metrics
- Reporting Dashboard
Training and fine-tuning Small Language Models using:
- Unsloth
- QLoRA
- Kaggle GPUs
- Google Colab
- Hugging Face
- Hugging Face
- Unsloth
- LangChain
- Ollama
- LM Studio
- vLLM
- Git
- GitHub
- Docker
- Linux
- VS Code
- Python Fundamentals
- Machine Learning Basics
- Deep Learning
- LLM Fundamentals
- Model Training at Scale
- AI Alignment Research
- Interpretability Research
- Open Source AI Contributions
Learn deeply. Build consistently. Share openly.
- GitHub: https://github.com/Anandhasasidharan
- LinkedIn: https://www.linkedin.com/in/asd01/
⭐ Building toward becoming an AI Engineer and Researcher.