About Me

 👋 Hi, I’m Heena Shaikh, a passionate data enthusiast and aspiring data analyst/scientist.

I have recently completed my  B.Sc DATA SCIENCE under Mumbai University through Bunts Sangha's S.M Shetty college in powai  this year in April2025 .

I specialize in Python, R,  MySQL, Power BI, Tableau, Advanced Excel, and have hands-on experience in machine learning, data visualization, and automated web scraping using UiPath and Selenium.

I’ve completed virtual internships with TATA and  British Airways via Forage, built real-world projects like e-commerce recommenders, dashboards, and predictive models.

I’m continuously upskilling and aim to make data-driven decisions impactful and insightful for businesses.

🎓 Virtual Internship Experience:

📄 Download my resume [Resume-Heena-Shaikh]








Comments

Post a Comment

How i built ShopeE-Mate

How I Built ShopeE-Mate (An E-commerce Product Recommendation /Comparison Using Python and Machine Learning)

Image
🛍️ Project Overview During my final year, I created a multi-platform e-commerce product recommendation system called ShopeE-Mate . This tool helps users find the best deals across Amazon, Flipkart, and JioMart — all in one place. 💡 The Problem Users waste a lot of time switching between apps and websites just to find the best price for the same product. I wanted to solve that using automation and ML/AI. 🛠️ Tools and Technologies Used 🔎 Web Scraping: RPA UiPath, Selenium 📊 Data Processing: Pandas, NumPy , Google colab 📦 Machine Learning: Scikit-learn, Tokenization(NLP) 🧠 Recommendation Models: Content-based, Collaborative, Hybrid  🌐 Web Framework: Flask  🛢 Database system : MySql XAMPP server ⚙️ How It Works Step 1: Product data is scraped in real-time using automation tools Step 2: Data is cleaned and structured using Pandas Step 3: ML models rank the products based on user preference, rating, and discount Step 4: Flask displays...
Read more

Sales Forecasting for Big Mart Using XGBoost Regression — A Machine Learning Approach

Image
  {Click on image for broad clear view} 🔍 Project Overview This project focuses on predicting sales for Big Mart stores across India using historical data. I built a machine learning model that analyzes factors like product price, store type, location, and promotions to forecast future sales with greater accuracy. 🎯 Business Problem Big Mart needed a reliable way to forecast sales to: Avoid overstocking and stockouts Optimize inventory and staffing Plan promotions more effectively Using machine learning helps make smarter, data-driven decisions. 🛠 Tools & Techniques Used Python + Google Colab Libraries: Pandas, Seaborn, Matplotlib, XGBoost, Scikit-learn Model Used: XGBoost Regressor Data Source: Kaggle – Big Mart Sales Dataset ⚙️ Key Steps I Followed Data cleaning and handling missing values Feature encoding (Label Encoding for categories) Exploratory Data Analysis using Seaborn Model training with XGBoost Evaluation usi...
Read more

Welcome to Decode With Heena

Image
I'm Heena Shaikh , a Data Science graduate with a passion for turning raw data into meaningful insights. Through this blog, I share my real-world projects, virtual internship experiences, and tutorials in data analytics, machine learning, and business reporting. Whether you're a recruiter, a fellow learner, or someone just curious about data — I'm glad you're here! 👉 Feel free to explore my About Me and Get my Resume , check out my Projects , check out my Blog Posts , or Contact Me anytime.
Read more