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vibeee45/README.md

Hi, I'm Vansh Bhardwaj 👋

Aspiring Data Scientist | Business Intelligence & Analytics

Typing SVG Animation
Email LinkedIn Kaggle GitHub

🚀 About Me

I'm a detail-oriented BCA student specializing in AI & Data Analytics at LNCT University, Bhopal, passionate about turning raw, messy data into clear, actionable business insight.

  • 🔭 Currently deepening my skills in predictive modeling, statistical analysis, and dashboarding
  • 🌱 Learning to connect technical data science work with real-world business objectives
  • 💬 Comfortable working across the full pipeline — from data cleaning to storytelling with visuals
  • 📫 Open to internships and entry-level roles in Data Science / Analytics / BI

🎓 Education
🏫 Program Bachelor of Computer Applications — AI & Data Analytics (BCA AIDA)
🏛️ Institution LNCT University, Bhopal
📅 Duration 2024 – 2027 (Ongoing)
🏆 Standing Department topper · CGPA: 9.22
📚 Coursework Machine Learning, Data Science, Statistics & Probability, Data Visualization, Advanced Mathematics

🛠️ Tech Stack & Skills

📌 Featured Projects

🤖 Machine Learning Algorithms

View Project

  • Objective: Built a growing collection of ML algorithms from scratch, from beginner to advanced level, documented in well-structured Jupyter Notebooks.
  • Coverage: Implemented supervised methods (Linear/Logistic Regression, Decision Tree, Random Forest, SVM, KNN, Naive Bayes) and unsupervised methods (K-Means, Hierarchical Clustering, DBSCAN, PCA).
  • Evaluation: Practiced model evaluation techniques — cross-validation, confusion matrices, precision/recall/F1, ROC-AUC, RMSE, and R².
  • Impact: Serves as a personal ML reference library and portfolio piece demonstrating both implementation and mathematical understanding.

🎬 Netflix Content Analysis

View Project

  • Objective: Investigated a dataset of 8,000+ Netflix titles to uncover trends in genres, formats, and regional production over time.
  • Data Processing & EDA: Conducted rigorous EDA with Pandas and NumPy — missing value imputation, data normalization, and feature extraction.
  • Impact: Synthesized findings into a structured report and slide deck to communicate insights clearly to non-technical stakeholders.

📱 Realme Smartphone Market Analysis

View Project

  • Objective: Analyzed a real-world Realme smartphone dataset to extract insights on pricing strategy, feature trends, and consumer preferences.
  • Data Processing: Performed end-to-end cleaning — handled missing values, removed duplicates, and standardized data types across multiple CSV files.
  • Exploratory Analysis: Used Pandas and NumPy to study price distributions, RAM/storage variation, and battery capacity trends.
  • Key Finding: Identified a strong correlation between higher specs and pricing spikes, and pinpointed the most preferred configurations in the mid-range segment.

📊 AEO Report Generator

View Project Live Demo

  • Objective: Built a full-stack web app with separate backend and frontend that generates AEO (Answer Engine Optimization) reports.
  • Architecture: Structured the project into distinct backend and frontend layers, deployed live for public use.
  • Impact: Delivered a working, deployed tool rather than just a notebook — bridging data analysis skills with product-style delivery.

🧹 Cleanytics — AI-Powered Data Cleaning & Analytics Platform

View Project

  • Objective: Designed a product concept and frontend for a platform that turns messy business spreadsheets into clean, dashboard-ready data.
  • User Flow: Built the experience around sign-in, CSV/Excel upload, automated cleaning, and dashboard review of results.
  • Stack: React frontend (Vite) with a planned FastAPI/Flask + PostgreSQL backend for authentication, file handling, and analytics APIs.
  • Status: Actively iterating — Version 2 added dashboard triggers, bug fixes, and a one-click local startup script.

📒 AccAI — AI-Powered Accounting Intelligence

View Project

  • Objective: Built an AI-powered accounting system that converts raw transaction data into structured journal entries and ledgers.
  • Automation: Automated generation of trial balances, Trading Account, Profit & Loss, and Balance Sheet from unstructured inputs.
  • Impact: Combined NLP/AI techniques with core accounting logic to reduce manual bookkeeping effort.

📊 How I Allocate Time in Data Science Projects

Time Allocation Animated Chart

This is a real animated chart (SVG + SMIL) — the donut draws itself and the legend bars grow in automatically on page load.

📈 GitHub Activity & Stats

GitHub Stats GitHub Streak
Top Languages
Thanks for stopping by — always happy to connect and talk data!

Pinned Loading

  1. Machine-Learning Machine-Learning Public

    Jupyter Notebook 8

  2. Netflix-analysis- Netflix-analysis- Public

    Jupyter Notebook 6

  3. Realme-Analysis Realme-Analysis Public

    Analyzed smartphone data from Realme 📱 to uncover insights on pricing and features. Performed data cleaning, EDA, and visualization using Python to identify trends in RAM, storage, and battery. Dem…

    Jupyter Notebook 4

  4. AEO-report-Generator AEO-report-Generator Public

    Python 6

  5. Cleanytics Cleanytics Public

    Python 4

  6. AccAI AccAI Public

    ACCAI is an AI-powered accounting intelligence system that converts raw transaction data into structured journal entries, ledgers, trial balances, Trading A/c, P&L and Balance Sheets. It combines N…

    Python 2