AI Misinformation Radar
An unsupervised AI threat-detection system designed to identify semantic anomalies and cluster potentially misleading claims using vector embeddings, dimensionality reduction, density clustering and local LLMs.
I work with Python, SQL, Power BI, Tableau and Machine Learning to transform raw data into actionable insights, interactive dashboards and intelligent applications.
A quick introduction to my background, interests and technical focus.
I'm Rimiya Rimshi K M, a Computer Science graduate with a strong interest in Data Analytics, Business Intelligence, Machine Learning and Generative AI.
I enjoy working with data from the point where unstructured information is transformed into clean datasets, meaningful analysis and interactive visualizations.
My technical work includes Python, SQL, Power BI, Tableau, Pandas, NumPy, Scikit-learn and AI technologies for building practical applications.
I'm particularly interested in solving practical problems through data — whether that's identifying business trends, building dashboards, developing predictive models or experimenting with AI-powered applications.
Kannur University
Power BI • SQL • Python
ML • GenAI • RAG
github.com/rimiya366
Public GitHub Repositories
Power BI & Tableau
Analytics & ML
GenAI & ML Applications
Combining analytical thinking, visualization and machine learning to build practical solutions.
Explore datasets, identify patterns, uncover trends and translate data into actionable insights.
Build interactive dashboards and reporting solutions using Power BI, Tableau and SQL.
Develop classification, regression and predictive models using Python and Scikit-learn.
Experiment with LLMs, RAG systems, embeddings and AI-powered applications.
A curated selection of analytics, business intelligence, machine learning and AI projects I've built.
An unsupervised AI threat-detection system designed to identify semantic anomalies and cluster potentially misleading claims using vector embeddings, dimensionality reduction, density clustering and local LLMs.
An autonomous local financial research assistant that processes financial information, extracts relevant tickers, retrieves market data and generates structured research insights through an AI workflow.
AI-powered resume and job-description matching application that performs ATS-style analysis and helps identify relevant skills and gaps.
A Power BI retail optimization project analyzing revenue, units sold, inventory conditions and overstock to identify business opportunities.
E-commerce sales analysis using Python and Power BI to explore sales performance and generate business insights from transactional data.
Interactive Tableau dashboard analyzing workforce data, employee attrition and key HR patterns to support data-driven workforce decisions.
Interactive Power BI dashboard analyzing accident trends, casualties, vehicle types, road conditions and safety patterns.
Data analytics project focused on exploring marketing campaign data, identifying patterns and extracting business-oriented insights.
Additional analytics, machine learning, deep learning and experimentation projects available on GitHub.
Retail sales analysis and Power BI dashboard.
Tableau dashboard exploring electric vehicle sales trends.
Sales performance analysis across regions and categories.
Customer churn analysis and Streamlit experimentation.
NLP experiment using a Bidirectional GRU architecture.
Sequence modelling using RNN, LSTM, Bi-LSTM and GRU.
Deep learning experimentation with CNN models.
Analysis of complaint volume and agency closure patterns.
See my complete collection of analytics, Python, SQL, machine learning and AI projects on GitHub.
View All GitHub RepositoriesI'm open to Data Analyst, Data Science, Business Intelligence and AI/ML opportunities.
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