Hello, I'm Yamin Hossain

A passionate data scientist with expertise in machine learning, statistical analysis, and data visualization. Turning complex data into actionable insights.

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About Me

Who I Am

I'm an aspiring data scientist with a passion for extracting meaningful insights from complex datasets. With a strong foundation in statistics, programming, and machine learning, I transform raw data into actionable business intelligence.

Machine Learning

Building predictive models and algorithms to solve complex problems.

Data Analysis

Extracting insights from large datasets using statistical methods.

Data Visualization

Creating compelling visual stories from complex data.

Research

Exploring new methodologies and staying current with the latest advancements.

Skills

My Expertise

A combination of technical proficiency and soft skills that enable me to deliver comprehensive data science solutions.

Technical Skills

Python90%

R70%

SQL85%

MATLAB60%

TensorFlow/PyTorch80%

Scikit-Learn85%

Pandas/NumPy90%

Tableau/Power BI80%

Big Data (Hadoop)65%

Skills Overview

Soft Skills

Problem Solving

Critical Thinking

Communication

Teamwork

Attention to Detail

Time Management

Adaptability

Continuous Learning

Featured Projects

AI Agents/Automation

FinanceAI

A comprehensive financial analysis platform built with Next.js that provides AI-powered insights for stocks, cryptocurrencies, and forex markets. The platform offers real-time market data, technical analysis, and personalized financial advice.

Next.js

Tailwind CSS

Shadcn UI

Chart.js

Lucide Icons

Twelve Data API

Reddit API

Agents

Code Live Demo

Cortex AI: Multi-Model Insights Hub

Developed a RAG-powered platform with multiple LLMs (DeepSeek, Qwen, LLaMA, OpenAI), achieving 98% retrieval accuracy and 40% lower response latency.

LangChain

ChatGroq API

LLM

Streamlit

MultiRAG

Search Agents

Code Live Demo

ReelSense AI: Intelligent Media Discovery & Recommendation

Created a Flask-based movie and TV show recommendation app using the API, featuring genre-based browsing and an AI-powered Agent. User can Also Track their favorite movies and TV shows.

Flask

TMDb API

Jinja2

Render

Multi-model

News API

PostgreSQL

Cloudinary

Code Live Demo

AI Automation Workflow Suite

A collection of production-ready n8n automation workflows powered by LLMs, designed to handle intelligent job-matching, personalized email generation, and daily AI-assisted reminders. The suite showcases end-to-end automation—including data extraction, multi-agent reasoning, third-party API integrations, and workflow orchestration—built for real-world productivity use cases.

n8n

Automation

AI Agents

Gemini API

Google Sheets

Telegram API

Notion API

API Orchestration

Code Live Demo

Real-Time Retail Forecasting with RAG-Powered AI

A production-grade MLOps ecosystem combining ML forecasting with RAG-based AI analytics. Features real-time data streaming every 10 minutes, nightly model retraining, incremental vector DB generation for 3M+ records, and an AI-powered Data Analyst capable of answering natural-language questions about sales, trends, and stores. Includes what-if simulations and a premium glassmorphism dashboard UI.

Streamlit

Python

XGBoost

Prophet

Redis

ChromaDB

Sentence Transformers

RAG

Groq API

Serverless MLOps

GitHub Actions

MLflow

Hugging Face Hub

Code Live Demo

Machine Learning/Deep Learning

Art Intelligence Hub

Multi-page application that showcases advanced deep learning models for art analysis. It includes two main tools: an Artwork Authenticity classifier to distinguish between AI-generated and human-made art, and an Art Style Ensemble Classifier that identifies the artistic style of a painting.

Keras

OpenCV

Grad-CAM

Transfer Learning

Ensemble Classifier

Code Live Demo

AI Content Classifier: Production MLOps Pipeline

A production-ready MLOps pipeline that automatically classifies Reddit content using advanced multi-label machine learning with enterprise-level automation and continuous learning.

content-classification

reddit-api

mlops-workflow

end-to-end-machine-learning

Code Live Demo

Sleep Disorder Detection App

Built a Streamlit-based Sleep Disorder Detection App using machine learning to predict sleep conditions like insomnia and sleep apnea based on user inputs. Integrated interactive analytics, personalized sleep tips, and deployed the app on Streamlit Cloud for accessible, data-driven sleep insights.

Scikit-learn

XGBOOST

Streamlit

Matplotlib/Seaborn/Plotly

Code Live Demo

Data Analysis

Supply Chain Analysis Dashboard

Developed a Streamlit-based dashboard to visualize key supply chain metrics like production volumes, stock levels, revenue, and costs.

Python

Pandas/Numpy

Matplotlib/Plotly/Seaborn

Streamlit Cloud

Code Live Demo

DVD Rental Analytics (Customer Behavior) Dashboard

A polished, local-first Streamlit dashboard for exploring the DVD Rental CSV dataset. Auto-load CSVs into an in-memory DuckDB and explore 25 built-in analytics queries, interactive Plotly visualizations, a saved-queries panel, and an Advanced SQL explorer.

Streamlit

DuckDB

Pandas

Plotly

SQL

Saved Queries

Local-first

Code Live Demo

NYC Subway Ridership Analysis Dashboard

An interactive web dashboard built with Streamlit to analyze and visualize live, hourly ridership data from the New York City MTA subway system.

nyc-opendata

Sodapy

DataGov

Powerbi

dashboard-application

Code Live Demo

Cardiac Care Performance

This project presents a comprehensive data analysis and interactive dashboard focused on Cardiac Surgery and Percutaneous Coronary Interventions (PCI) performance by hospital, spanning from 2008 onwards.

Healthcare data

DataGov

Feature Engineering

Plotly-express

tableau-public

Code Live Demo

Customer Insights and Regional Sales Dashboard

This dashboard provides an interactive and comprehensive analysis of customer behavior, regional sales trends, and revenue insights.

Sale-analysis

Duckdb

Feature Engineering

Customer Segmentation

Sales-dashboard

Code Live Demo

Avocado Shiny Dashboard

Developed a Shiny-based Avocado Dashboard to analyze California avocado production and value using interactive visualizations. Deployed on a Shiny server, enabling real-time insights, with support for local deployment using Uvicorn.

Shiny for Python

Pandas/NumPy

Shiny Server/Uvicorn

Matplotlib/Seaborn/Plotly

Code Live Demo

Netflix Insights Genre Trends Analysis

Conducted an in-depth analysis of the Netflix dataset using SQL to extract insights on genres, languages, countries, and IMDb score trends. Utilized advanced SQL queries, statistical analysis, and visualized findings with Tableau and Looker Studio to explore content distribution and directorial performance.

SQL(MySQL)

SQL Aggregations

Tableau/Looker Studio

Pandas

Code Live Demo

Analyzing Employee’s Performance for HR Analytics

Performed an in-depth HR analytics study using SQL to analyze employee performance, covering demographics, training effectiveness, KPI achievements, and service duration. Visualized key insights with Power BI dashboards, enabling data-driven decision-making for workforce optimization.

SQL(Microsoft SQL Server)

SQL Aggregations

Power BI

Pandas

Code Live Demo

Research

Publications

My contributions to academic research and scientific literature in data science and machine learning.

Machine Learning for Computer Vision: A Comprehensive Overview

Abdullah Ibnah Hasan, Nayem Uddin Prince, Md. Kamrul Siam, Md. Maruf Miah, Md. Miskat Hossain Siddique, Yamin Hossain, Md. Habibur Rahman

2025

International Conference On Data Mining And Information Security (ICDMIS 2024), pp. 93–104

This paper focuses on detecting sports types from images, which can be used for action recognition. Detecting small objects like athletes and sports equipment is challenging due to their varying colors, appearances, and distance from the camera. CNN is the most common detection tool for sports, but it struggles with image accuracy due to various angles and light conditions

Neural network

Image processing

Computer vision

Feature extraction

Machine learning

Pattern recognition

DOI: 10.1007/978-981-96-6053-7_7

View Publication

Improving Sports Categorization in WiFi- Blocked Areas: Modifying YOLO Network for All-Inclusive Sports Image Identification

Md. Habibur Rahman, Samar Das, Mahtab Uddin, Aminul Islam, Yamin Hossain, Abdullah Hafez Nur, Md. Abdullah

2025

4th International Conference on Machine Learning, IoT and Big Data (ICMIB 2024), pp. 229–242

Deep Learning

object detectio

YOLO

CNN

DOI: 10.1007/978-981-96-3797-3_19

View Publication

YOLOv8 Image Processing for Evaluation of Stability Algorithms Based on Neural Networks: A Sports Use Case

Md. Habibur Rahman, A. S. M. Mohiul Islam, Abdullah Ibnah Hasan, Mahtab Uddin, Ashek Ahmed, Asif Ahammad Miazee, Yamin Hossain

2024

International Conference on Inventive Communication and Computational Technologies (ICICCT 2024), pp. 613–622

Sports image classification is a complex problem with many different sports involved. It has subpar detection performance and challenges with feature recognition.

Deep learning

YOLOv8

Neural network

Sports Image Classification

Computer vision

DOI: 10.1007/978-981-97-7710-5_46

View Publication

Qualifications

Education & Certifications

Education

Bachelor of Science in Computer Science

Vellore Institute of Technology, Andhra Pradesh

CGPA: 8.36 / 10 (Indian Grading System)

2021 - 2025

Focused on programming fundamentals, algorithms, and data structures. Minor in Mathematics. Specialization in data analytics.

Key Courses:

Data Structures & Algorithms

Probability & Statistics

Linear Algebra

Operating Systems

Object-Oriented Programming

Database Management System

Computer Architecture

Computer Networks

Software Engineering

Optimization Techniques

Data Warehousing & Data Mining

Mining Massive Datasets

NoSQL Database

Application of Data Analytics

Club Activities & Extracurriculars

LIT-DAC Club(Live Innovate and Transform - Data Analytics)
Marketing Team Member • 2022 - 2023
Promoted seminars and events, increasing participation by 40%. Showcased marketing and public speaking skills, creating an engaging environment.
CSI VITAP CHAPTER
Management Team • 2021 - 2022
Organized tech events and led a team to enhance community service and academic initiatives, fostering unity among 30+ members

Certifications

AI Agents Fundamentals
Hugging Face • 2025
Applications of AI for Predictive Maintenance
NVIDIA • 2024
Building Transformer-Based Natural Language Processing Applications
NVIDIA • 2024

Continuous Learning

I'm committed to continuous learning and staying updated with the latest advancements in data science and AI.

Currently enrolled in specialized courses on deep learning, natural language processing, and computer vision to expand my skill set and tackle more complex data challenges.

Get in Touch

Contact Me

Have a project in mind or want to discuss a data science opportunity? Feel free to reach out!

Send a Message

Fill out the form below and I'll get back to you as soon as possible.

Contact Information

Feel free to reach out through any of these channels.

Email

issan.yamin@gmail.com

robinmill4d@gmail.com

Phone

+91 (630) 101-1373

+880 (197) 794-0357

Location

Andhra Pradesh, India

Dhaka, Bangladesh

Hello, I'm Yamin Hossain

Who I Am

Machine Learning

Data Analysis

Data Visualization

Research

My Expertise

Technical Skills

Skills Overview

Soft Skills

Featured Projects

AI Agents/Automation

Machine Learning/Deep Learning

Data Analysis

Publications

Education & Certifications

Education

Key Courses:

Club Activities & Extracurriculars

LIT-DAC Club(Live Innovate and Transform - Data Analytics)

CSI VITAP CHAPTER

Certifications

AI Agents Fundamentals

Applications of AI for Predictive Maintenance

Building Transformer-Based Natural Language Processing Applications

Continuous Learning

Contact Me

Email

Phone

Location