abhishek = {
"degree" : "B.Tech Computer Science Engineering — 2nd Year @ LPU",
"location" : "Punjab, India 🇮🇳",
"focus" : ["Data Engineering", "Machine Learning", "Backend Development"],
"learning" : ["Spring Boot", "Spring MVC", "REST APIs", "System Design"],
"goal" : "Land a Data Engineering role at a product-based company",
"fun_fact" : "I enjoy wrangling data more than building UIs 😄"
}Binary classification model to predict credit risk on the UCI German Credit Dataset
- Built full ML pipeline: Data Loading → EDA → Preprocessing → Training → Evaluation
- Achieved 77.58% accuracy on 1,000 loan applicants using Logistic Regression
- Visualized feature correlations, distributions & confusion matrix with Seaborn & Matplotlib
- Saved trained model as
.pkl— Flask/Streamlit deployment in Future Scope
Python Pandas Scikit-learn Matplotlib Seaborn Jupyter
Interactive dual-page Power BI dashboard analyzing 1,473 employees to uncover causes of 16.1% attrition
- Analyzed attrition across age, salary, department, job role, gender & education dimensions
- Built 7 chart types — Donut, Matrix, Line/Area, Stacked Bar, Grouped Bar, Column
- Created DAX measures for Attrition Rate, Avg Salary, Avg Tenure KPIs
- ETL done via Power Query: cleaning, type validation, feature engineering (AgeGroup, SalarySlab)
- Live dashboard published on Power BI Service with QR code access
Power BI DAX Power Query ETL Data Visualization Excel
AI-powered chatbot that suggests 3 movies with posters based on your genre or mood
- Integrated Groq LLaMA 3.3 70B via API for intelligent movie recommendations
- Fetched real movie posters dynamically using OMDB API
- Engineered prompts to control AI output format, domain-lock & avoid session repeats
- Deployed live on Render — fully functional with dark theme UI
Python Flask Groq API LLaMA 3 OMDB API Prompt Engineering HTML/CSS/JS
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Currently Learning 🌱
From: 03 May 2026 - To: 10 May 2026
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"Data is the new oil — I'm here to build the pipelines." 🚀
