class AasimAnsari:
def __init__(self):
self.name = "Mohd Aasim Ansari"
self.role = "Aspiring Data Scientist & AI Engineer"
self.expertise = ["Data Science", "Machine Learning", "Deep Learning",
"NLP", "Computer Vision", "Gen AI", "RAG Pipelines",
"Agentic AI", "Multi-Agent Systems", "Full Stack Development"]
self.stack = {
"Data Science" : ["Pandas", "NumPy", "scikit-learn", "XGBoost",
"TensorFlow", "PyTorch", "Matplotlib", "Seaborn"],
"Gen AI" : ["LangChain", "LangGraph", "OpenAI API", "HuggingFace",
"RAG", "Groq", "Ollama", "LlamaIndex"],
"Agentic AI" : ["CrewAI", "AutoGen", "LangGraph", "Multi-Agent Systems"],
"Full Stack" : ["Python", "React", "FastAPI", "Node.js", "MongoDB",
"TailwindCSS", "Flask", "TypeScript"],
}
self.current_focus = "Full Stack Data Science with Gen AI and Agentic AI"
self.open_to = ["Full-Time Roles", "Internships", "Open Source Contributions", "Collaborations"]
def __repr__(self):
return "Always learning. Always building. Always delivering. π"| π¬ ChatNova AI | Full-stack ChatGPT SaaS with auth & streaming | React Β· Node.js Β· OpenAI API | | π€ Agentic RAG Chatbot | Multi-agent RAG with memory & tool use | LangChain Β· LangGraph Β· CrewAI | | π SalesCast AI | AI forecasting Β· XGBoost Β· ARIMA Β· Prophet Β· LSTM | React Β· FastAPI Β· SQLite | | π§ ML Interview Prep | 500+ Q&A Β· cheat sheets Β· system design | Python Β· PyTorch Β· scikit-learn | | π€ AI Resume Screener | Screen 100s of resumes instantly, rank by job fit | Python Β· spaCy Β· Flask | | π¦ Smart Traffic System | YOLOv8 adaptive signals + emergency override | YOLOv8 Β· OpenCV | | π¨ Disaster Alert System | Real-time geo alerts via Socket.IO + Leaflet | Socket.IO Β· MongoDB |




