class DataScientist:
def __init__(self):
self.name = "P Samson Silvester"
self.role = "Data Scientist & Gen AI / LLM Engineer"
self.location = "Bengaluru, Karnataka, India"
self.education = "Master's in Computer Science from Woolf University"
self.currently_learning = ["LLMs", "RAG Applications", "GenAI","AI Automations","Prompt Engineering"]
self.interests = ["Machine Learning","MLOps", "Deep Learning", "Time Series", "NLP","Recommendation Systems"]
def say_hi(self):
print("Thanks for dropping by! Let's build something amazing together!")
me = DataScientist()
me.say_hi()
🔭 Currently Working On: n8n workflow automation, prompt engineering for LLMs, ML projects (fraud detection, demand forecasting), and daily Python/SQL practice
🤝 Open to Collaborate On: Data Science projects, ML pipelines, GenAI applications, and open-source contributions
💡 Looking For Help With: Distributed ML systems, real-time inference optimization, and cloud-native architectures
🌱 Currently Learning: LLMs, RAG frameworks, MLOps best practices, and advanced deep learning
💬 Ask Me About: Python, Machine Learning, Data Science, MLOps, TensorFlow, PyTorch, AWS
📫 Reach Me: samsonsilversterp@gmail.com
📝 Read My Blog: Medium
⚡ Fun Fact: I believe every dataset has a story to tell - you just need to ask the right questions!
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1. Machin Learning Projects
| Project | Description | Tech Stack | Status |
|---|---|---|---|
| 🧪 AB Testing Framework | Statistical analysis platform for experiment design and causal inference | Python, SciPy, Statsmodels | ✅ Complete |
| 👥 Customer Segmentation | RFM analysis for targeted marketing and customer insights | Python, Sklearn, Plotly | ✅ Complete |
| 🚨 Fraud Detection System | Real-time anomaly detection using unsupervised learning | TensorFlow, Isolation Forest | ✅ Complete |
| 📊 Demand Forecasting | Time series forecasting for supply chain optimization | Prophet, LSTM, XGBoost | ✅ Complete |
| 💬 Sentiment Analysis | NLP pipeline for airline customer sentiment | BERT, Transformers, NLTK | ✅ Complete |
2. AI Projects
| Project | Description | Tech Stack | Status |
|---|---|---|---|
| 🤖 LLM & RAG Application | GenAI application with retrieval augmented generation | LangChain, OpenAI, FAISS | ✅ Complete |
| 📈 AI Multi-Agent Trading Firm | Multi-agent trading system with risk controls, paper execution, and audit logging | LangGraph, Streamlit, Docker, Alpaca, Supabase, SQLite | ✅ Complete |
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🚀 Build 3 production-ready ML systems with full MLOps pipeline
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🌟 Contribute to 5 major open-source ML/AI projects
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📚 Master advanced LLMOps and prompt engineering
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🎤 Speak at data science conference or meetup
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📝 Publish 12 technical blog posts on ML best practices
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🏆 Complete research papers on ML and AI
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👥 Mentor 10+ aspiring data scientists, Data Analysts and Business Analysts
📖 Check out my articles on Medium
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🔥 Coming Soon: "Github repo's to master Gen AI Engineering"
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📊 Coming Soon: "Issue's & Solutions on MLOPs Pipelines"
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🤖 Coming Soon: "Best practises to code using Python"
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💡 Coming Soon: "Best Practises on Agentic AI, Automation, use cases of Agents"
🔧 n8n Automation ████████████░░░░░░░░ 60% (Workflow automation & integrations)
🤖 Prompt Engineering ██████████░░░░░░░░░░ 50% (LLM optimization & RAG systems)
🐍 Python Problem Solving████████░░░░░░░░░░░░ 40% (Data structures & algorithms)
📊 SQL Queries ███████░░░░░░░░░░░░░ 35% (Database optimization & practice)
📚 Learning & Research █████░░░░░░░░░░░░░░ 25% (New tools & technologies)
Current Focus Areas:
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🔄 Building automation workflows with n8n for data pipelines
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💡 Experimenting with prompt engineering techniques for better LLM outputs
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🧩 Solving Python coding challenges (algorithms, data structures)
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🗄️ Practicing SQL queries for complex data analysis
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📖 Exploring GenAI tools and frameworks
💡 "Data is the new oil, but insights are the refined fuel that powers smart decisions."
⭐️ From RedSamurai07 | Made with ❤️ and ☕
What is the updated code I want the updated code for github readme with this circular dp file name and also needed under Machine learning projects (attached in image 2