Check out all my latest and most high valued Industry Standard Projects Check it out here
| Field | Project Name | GitHub Link |
|---|---|---|
| π€ AI | YouTube Chatbot using Transcripts with GroqLLM | π |
| π ML | Sentiment Analysis using Stock Data NLP | π |
| π ML | SMS Spam Classification using Naive Bayes, Decision Tree, and Random Forest | π |
| βοΈ ML | Fuel Consumption Prediction API using Linear Regression and FastAPI | π |
| π DL | FastAPI Implementation with Streamlit on IRIS Dataset | π |
| π¬ ML | Movie Genre Classification with Multi-label Output | π |
| π NLP | Restaurant Review Sentiment Analysis | π |
| π° ML | Bitcoin Price Prediction using SVR | π |
| Airline Time Series Forecasting using LSTM | π | |
| π Web | PCMartBD | π |
| π Blog | Continuous-Learning-Blog | π |
| π§ Contact | mdsameersayed0@gmail.com | π§ |
python tensorflow pytorch pandas numpy scikit-learn keras matplotlib seaborn spacy mysql postgresql streamlit fastapi html5 css3 javascript php
AI and Machine Learning Developer skilled in designing, training, and deploying end-to-end data-driven solutions. Experienced in building NLP chatbots, sentiment analysis models, predictive analytics systems, and time-series forecasting using Python, TensorFlow, scikit-learn, and LangChain. Proficient in developing and integrating ML APIs with FastAPI and Streamlit for real-time inference. Strong foundation in data preprocessing, feature engineering, and model optimization. Passionate about applying AI to solve real-world problems and continuously improving through hands-on experimentation with emerging frameworks and tools.
- Large Language Models & AI Chatbots: Developing LLM-powered applications like YouTube transcript chatbots using LangChain, FAISS, and GroqLLM, integrated with FastAPI for real-time Q&A and chat logging.
- Natural Language Processing & Sentiment Analysis: Building NLP pipelines for applications such as stock data sentiment correlation, restaurant review analysis, and multi-label movie genre classification, leveraging Python, NLTK, Scikit-learn, and TF-IDF features.
- Machine Learning & Predictive Modeling: Implementing models for tasks like SMS spam classification, fuel consumption prediction, Bitcoin price forecasting (SVR), and airline passenger time series forecasting (LSTM), with end-to-end pipelines including preprocessing, training, and evaluation.
- API Development & Full-Stack Integration: Deploying machine learning models via FastAPI and integrating with frontends like Streamlit for real-time predictions and interactive visualization.
- Programming Languages: Python, PHP, JavaScript, C#, SQL
- Frameworks & Libraries: Django, Flask, Laravel, Scikit-Learn, TensorFlow, Tailwind CSS, LangChain, FastAPI, Streamlit
- Databases: MySQL, SQL Server, MongoDB
- Cloud & Deployment: AWS, Azure, GroqLLM
- Data & ML Tools: Pandas, NumPy, NLTK, FAISS, Matplotlib, Seaborn, TF-IDF, Support Vector Regression (SVR), LSTM
- Projects Integration: YouTube Chatbot using GroqLLM, Sentiment Analysis on Stock Data, SMS Spam Classification, Fuel Consumption Prediction API, Movie Genre Classification, Restaurant Review Sentiment Analysis, Bitcoin Price Prediction, Airline Time Series Forecasting