Skip to content
View anandshenoy29's full-sized avatar

Block or report anandshenoy29

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don’t include any personal information such as legal names or email addresses. Markdown is supported. This note will only be visible to you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
anandshenoy29/README.md

Hello, I'm Anand Shenoy! 👋🏻

Passionate MSc IT student with a strong foundation in Artificial Intelligence, Machine Learning, Data Analytics and Visualization. Proficient in Python, SQL, and statistical modeling, with a current focus on applying Generative AI and Agentic AI frameworks to transform raw data into actionable intelligence. Currently seeking entry-level opportunities where I can apply my skills to impactful projects and solve real-world problems.

🛠️ SKILLS

Category Skills
Programming Languages Python, Java, JavaScript
Artificial Intelligence & GenAI LLMs, Agentic Workflows, RAG, Prompt Engineering
Python Libraries NumPy, Pandas, Matplotlib, Seaborn, Scikit-Learn, LangChain
Web Technologies/Frameworks HTML, CSS, Flask, Streamlit
Data Storage & Visualization MySQL, ChromaDB, Pinecone, MS Excel
Tools & Platforms Nodemation (n8n), VS Code, Jupyter Notebook, Git

Pinned Loading

  1. multi-context-research-assistant-project multi-context-research-assistant-project Public

    Built an AI agent-powered dual-workflow RAG system on n8n platform for accurate multi-document analysis using OpenAI's gpt-4o-mini, integrating automated Google Drive ingestion, Pinecone vector sto…

    Python

  2. context-aware-research-assistant-project context-aware-research-assistant-project Public

    Built an AI agent-powered RAG web application for accurate document analysis using Python and LangChain, integrating Google's Gemini 2.5 Flash and ChromaDB for intelligent semantic retrieval, dynam…

    Python

  3. sleep-quality-prediction-research-project sleep-quality-prediction-research-project Public

    Developed a machine learning model to predict sleep quality from lifestyle data using Scikit-Learn, achieving 85.19% accuracy and an 0.88 ROC-AUC score with an optimized Random Forest classifier, v…

    Jupyter Notebook