I build practical AI systems — from classical ML models to deep learning architectures, LLM-based solutions, quant trading research, and deployed MLOps pipelines.
I don't just “learn AI”, I ship AI projects consistently.
- 🧠 LLM Apps, GenAI Pipelines, RAG
- ⚙️ MLOps: FastAPI, CI/CD, Model Serving
- 📈 Quantitative Analysis & ML Trading Models
- 📊 Advanced ML & Deep Learning Projects
- 🔍 AI Automation & Agency Solutions
- Scikit-Learn • XGBoost • Feature Engineering
- Regression, Classification, Clustering
- TensorFlow • PyTorch
- CNN • RNN • LSTM • BiLSTM
- OpenAI API • LangChain • Embeddings • Vector Search
- Prompt Engineering • RAG Pipelines
- FastAPI • Flask
- Render • HuggingFace Spaces
- Git • Linux
- Pandas • NumPy
- TA-Lib • Statsmodels
- Market Indicators • Backtesting Basics
End-to-end ML pipeline using RF/XGBoost.
TF-IDF + similarity scoring for role matching.
Prediction/classification of traffic conditions.
Clean regression workflow with low error.
Multiple ML models compared and optimized.
Data cleaning, correlations, insights.
- 🔗 LinkedIn: www.linkedin.com/in/sheshpalsingh915
- 🐙 GitHub: https://github.com/sheshpalsingh01