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Working on practical AI and data-driven projects
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Working on practical AI and data-driven projects

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sameer-at-git/README.md

🚀 Md. Sameer Sayed


🤖 Machine Learning & AI Engineer | Data-Driven Problem Solver | Full Stack ML Developer

Profile ViewsGitHub FollowersGitHub Stars


🌟 Project Portfolio

🎯 Explore all my latest and industry-grade AI & ML projects here:
👉 View My Portfolio Website


🧠 Projects Index

FieldProject NameGitHub Link
🤖 AIYouTube Chatbot using Transcripts with GroqLLM🔗
📈 MLSentiment Analysis using Stock Data NLP🔗
📊 MLSMS Spam Classification using Naive Bayes, Decision Tree, and Random Forest🔗
⚙️ MLFuel Consumption Prediction API using Linear Regression and FastAPI🔗
📊 DLFastAPI Implementation with Streamlit on IRIS Dataset🔗
🎬 MLMovie Genre Classification with Multi-label Output🔗
📝 NLPRestaurant Review Sentiment Analysis🔗
💰 MLBitcoin Price Prediction using SVR🔗
✈️ DLAirline Time Series Forecasting using LSTM🔗
🛒 WebPCMartBD🔗
📝 BlogContinuous-Learning-Blog🔗
📧 Contactmdsameersayed0@gmail.com📧

🌐 Connect with Me


⚙️ Languages & Tools


💡 About Me

Building AI that solves real-world problems — not just models that run in notebooks.
I specialize in NLP, LLMs, and ML deployment using FastAPI, Streamlit, and LangChain.
Focused on scalable AI integration for production.


🎯 Focus Areas

💬 NLP & LLMs⚡ Predictive ML☁️ API Deployment📊 Data Visualization
LangChain, GroqLLM, FAISSRegression, Classification, LSTMFastAPI, Streamlit, AWSMatplotlib, Seaborn, Plotly

🧰 Tech Stack Breakdown


📊 GitHub Analytics

GitHub StatsContribution Graph


🧩 What I’m Exploring


🏆 Achievements

GitHub Trophies


Fun Stats

Contributor Stats


⭐ Let's Collaborate on AI Projects! ⭐


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  1. PCMartBD-e-Commerce-Platform-for-PC-Hardware-and-Repairing PCMartBD-e-Commerce-Platform-for-PC-Hardware-and-RepairingPublic

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    My Github Profile page , please do make sure to Star Repos

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    A gesture-controlled media player using Arduino and sensors to manage playback (play, pause, skip, volume) through intuitive hand gestures instead of buttons.

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    This project uses the ARIMA model to predict future energy demand based on historical data. It includes data preprocessing, model training, and forecasting, with easy-to-follow steps for running th…

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    Predicting customer churn using machine learning techniques. It includes data preprocessing, model training, and evaluation using the Telco Customer Churn dataset. The repository contains a Jupyter…

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