class AaricaRaj:
def __init__(self):
self.role = "Data Science & AI"
self.education = "BCA; 2nd Year Undergraduate"
self.location = "Jamshedpur, India"
self.contact = "shrivastavarchana57@gmail.com"
self.domain = ["Data Analytics", "NLP", "RAG Systems",
"Deep Learning", "MLOps", "Multimodal AI"]
self.stack = {
"languages" : ["Python", "SQL", "MySQL",
"JavaScript (basic)"],
"data_analytics" : ["Pandas", "NumPy", "Matplotlib",
"Seaborn", "Excel", "Power BI basics"],
"ai_ml" : ["LLMs", "RAG", "Transformers",
"Computer Vision", "Generative AI"],
"frameworks" : ["LangChain", "HuggingFace", "PyTorch",
"Scikit-learn", "Flask", "Gradio"],
"vector_search" : ["FAISS", "all-MiniLM-L6-v2",
"Semantic Embeddings"],
"cloud_apis" : ["Azure AI", "HuggingFace Spaces",
"Groq API", "Gemini API", "REST APIs"],
"mlops" : ["Docker", "Git", "GitHub",
"Jupyter", "Google Colab"],
}
def current_focus(self):
return [
"Data analysis with Python, SQL and visualization tools",
"Prepping for Data Analyst roles; EDA, dashboards, storytelling",
"Production RAG pipelines; FAISS + LangChain + Groq",
"Fine-tuning DistilBERT and RoBERTa for NLP tasks",
"End-to-end MLOps: train, containerize, deploy, monitor",
]
def open_to(self):
return [
"Data analytics projects and collaborations",
"AI/ML research and open-source contributions",
"Transformer fine-tuning and RAG systems",
"Student researcher and internship opportunities",
]
|
AI-powered carbon footprint platform; Hackathon build
|
Ask questions over any PDF using semantic search + LLM
|
|
Transformer fine-tuning for emotion and sentiment classification
|
End-to-end ML with Docker and a 3D particle UI
|
|
3D neural network you control with your hands; no install needed
|
A browser game built with pure HTML, CSS and JS
|
|
Neon tube cursor animation using WebGL
|
Math-inspired generative art with Python's Turtle library
|
|
Multimodal AI; Vision Transformer + BERT
|
|
| Metric | Value | What it means |
|---|---|---|
| Live AI Systems | 4+ | Deployed on HuggingFace Spaces and PythonAnywhere |
| Best Model Accuracy | 91.3% | DistilRoBERTa fine-tuned for 7-class emotion classification |
| Latency Reduction | 60x | RAG pipeline dropped from 30s+ to ~0.5s with Groq |
| Model Scale | 247M params | Salesforce BLIP multimodal implementation |
| Certification | Azure AI | Microsoft certified; 2025 |
| Vector Search | FAISS | Semantic retrieval on custom document corpora |
| Degree | Institution | Status |
|---|---|---|
| Bachelor of Computer Applications (BCA) | Jamshedpur | 2nd Year (Ongoing) |
| Certification | Issuer |
|---|---|
| Azure AI Fundamentals | Microsoft |
|
|
|
|
🔗 Professional
|
💻 Development
|
📧 Contact |
📧 Email | 📍 Jamshedpur, India 🇮🇳
🔭 Currently building: Data analytics skills; SQL, EDA, dashboards, storytelling with data. Also building RAG systems and fine-tuning transformers on the side!
💡 Philosophy: Understand the data first; then let the model do the talking.
⭐ If my projects helped you, a star means a lot!
