class AasimAnsari:
def __init__(self):
self.name = "Mohd Aasim Ansari"
self.role = "Data Scientist | ML Engineer | AI Researcher | Full Stack Developer"
self.expertise = [
"Machine Learning", "Deep Learning", "NLP",
"Computer Vision", "LangChain", "RAG", "Agentic AI",
"YOLOv8", "Data Analysis", "Full Stack Development"
]
self.stack = {
"Data Science" : ["Python", "Pandas", "NumPy", "Matplotlib", "Seaborn", "Plotly"],
"AI / ML" : ["scikit-learn", "TensorFlow", "PyTorch", "LangChain", "YOLOv8", "OpenCV"],
"Web Dev" : ["React", "Node.js", "TypeScript", "MongoDB", "Express", "Flask"],
}
self.email = "mohdaasimansari2003@gmail.com"
self.available = True # Open to Internship Β· Research Β· Freelance
def __repr__(self):
return "Always learning. Always building. Always delivering."| # | Project | Description | Tech Stack | Status |
|---|---|---|---|---|
| 1 | 𧬠Disease Prediction System | ML model predicting diseases from symptoms | Python, scikit-learn, Flask | |
| 2 | π Stock Price Forecasting | LSTM-based stock trend prediction | PyTorch, Pandas, Plotly | |
| 3 | π Sentiment Analysis Engine | NLP-powered social media sentiment classifier | BERT, HuggingFace, Python | |
| 4 | π YOLOv8 Object Detector | Real-time object detection pipeline | YOLOv8, OpenCV, Python | |
| 5 | π House Price Predictor | Regression model with EDA & deployment | XGBoost, Flask, Seaborn | |
| 6 | π€ RAG Chatbot | LangChain RAG pipeline over custom docs | LangChain, OpenAI, FAISS | |
| 7 | π EDA Dashboard | Interactive data exploration app | Streamlit, Plotly, Pandas | |
| 8 | πΎ Crop Recommendation AI | AI system for smart agriculture | Random Forest, Flask, NumPy |