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Achievements

Achievement: Pair ExtraordinaireAchievement: Pull SharkAchievement: YOLOAchievement: Quickdraw

Achievements

Achievement: Pair ExtraordinaireAchievement: Pull SharkAchievement: YOLOAchievement: Quickdraw

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Immanuel2004/README.md

About Me

Currently Working On
Developing AI-powered applications leveraging Generative AI, Agentic AI, Natural Language Processing, and Computer Vision, with a strong emphasis on real-world impact and assistive technologies. Looking to Collaborate On
Open-source AI initiatives, intelligent agent systems, Generative AI applications, and innovative machine learning solutions that address meaningful challenges. Seeking Help With
Scaling AI-driven systems, deploying autonomous AI agents, and advancing research in multimodal intelligence and agentic workflows. Currently Learning
Advanced concepts in Generative AI, Agentic AI architectures, LLM orchestration, Retrieval-Augmented Generation (RAG), and scalable AI system design. Ask Me About
Machine Learning, Deep Learning, NLP, Computer Vision, Generative AI, Agentic AI, and end-to-end AI product development.

Socials:

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Tech Stack:

Python C TensorFlow PyTorch Scikit Learn Matplotlib Django Flask FastAPI AWS Docker Kubernetes Firebase Vercel Netlify Heroku MongoDB MySQL SQLite Redis Git GitHub GitLab GitHub Actions Jenkins Postman Kafka Plotly Figma Canva Arduino Markdown LaTeX LangChain HuggingFace Pinecone Ollama LlamaIndex MLflow Airflow DVC Pandas NumPy Keras Streamlit Power BI LangGraph OpenAI ChromaDB Weaviate

GitHub Stats:



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  1. Dataflow-Deployment Dataflow-Deployment Public

    Python 1

  2. DIT DIT Public

    GenAI application that analyzes CSV, JSON, Excel, and other datasets to perform data preprocessing, generate dynamic insights, build ML models, create visualizations, compare datasets, and generate…

    Python 1

  3. ML-project ML-project Public

    Jupyter Notebook 1

  4. RNN-SentimentAnalysis RNN-SentimentAnalysis Public

    Jupyter Notebook 1

  5. Self-Reflective-RAG Self-Reflective-RAG Public

    A self-reflective RAG Bible Q&A app that ingests Scripture, retrieves relevant passages, and generates answers with citations in a Streamlit interface.

    Python