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Data Scientist | ML & NLP | Python · Scikit-learn · Streamlit
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Data Scientist | ML & NLP | Python · Scikit-learn · Streamlit
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Sankesh12/README.md

Hi there 👋, I'm Sankesh Lal

Data Scientist | ML & NLP | Python · Scikit-learn · Streamlit

🧑‍💻 About Me

  • Data Scientist with hands-on experience in Python, Machine Learning, and NLP. Built end-to-end projects including spam detection, sentiment analysis, and laptop price prediction systems. Skilled in Pandas, Scikit-learn, Streamlit, and data visualization. Experienced in building and deploying ML applications with performance up to 97% accuracy.

Career Goal: Seeking internship and full-time opportunities to build strong expertise in data science, machine learning, and AI while contributing to impactful projects, with the goal of growing into a successful Data Scientist.

🛠 Skills & Tools

Programming Data Analysis Machine Learning Tools
Python 🐍 Pandas, NumPy, Matplotlib, Seaborn and EDA Scikit-learn, Regression & Classification Git, GitHub, Jupyter and VS Code

Upcoming Skills:

  • Advanced SQL & Database Management
  • Deep Learning & Neural Networks
  • Generative AI Applications & LLMs
  • Agentic AI Systems & AI Automation

🚀 Featured Projects

🎬 Movie Blockbuster Prediction

  • Developed a Movie Success Prediction system using the TMDB dataset to analyze movie trends and estimate movie performance.
  • Performed data cleaning, EDA, feature engineering, and applied Linear Regression, Random Forest, TF-IDF, and KMeans for revenue prediction, movie analysis, and clustering.
  • Deployed a Streamlit web app for real-time blockbuster prediction.
  • 🔗 movie-blockbuster-prediction

💻 Laptop Price Predictor

  • Built a laptop price prediction pipeline to estimate market prices based on key hardware features, comparing multiple regression models where XGBoost achieved the best performance with an R² score of 0.87.
  • Applied feature engineering and EDA using Pandas, NumPy, Matplotlib, and Seaborn.
  • 🔗 laptop-price-predictor

📧 Email/SMS Spam Classification

  • Developed an NLP-based Email/SMS Spam Detection system to identify and filter unwanted messages, achieving 97% accuracy and 94% precision using Multinomial Naive Bayes.
  • Compared 5 ML models and evaluated performance using key classification metrics.
  • Deployed a real-time spam classification web app with Streamlit Cloud.
  • 🔗 email/sms-spam-classification

🎥 Movie Review Sentiment Analysis

  • Predicted positive and negative sentiment from customer reviews and feedback using TF-IDF vectorization on 50,000 IMDb reviews.
  • Logistic Regression achieved 88% test accuracy, outperforming other models through evaluation using accuracy and confusion matrix metrics.
  • Deployed an interactive Streamlit app for real-time sentiment prediction.
  • 🔗 movie-review-sentiment-analysis

🎓 Education & Certifications

  • Bachelors in Computer Science – Shah Abdul Latif University (2020–2023)

🌟 Interests & Soft Skills

  • Problem-solving, Collaboration, Creativity, Time-management, Adaptability and Communication 💡

📫 Contact:

📊 GitHub Stats

Sankesh's GitHub Stats

Popular repositories Loading

  1. House-Price-Prediction House-Price-Prediction Public

    • Created a House Price Prediction system using housing and location data with preprocessing, feature engineering, and Random Forest regression. • Deployed a Streamlit app for real-time price predi…

    Jupyter Notebook 1

  2. Movie-Review-Sentiment-Analysis Movie-Review-Sentiment-Analysis Public

    • Predicted positive and negative sentiment from customer reviews and feedback using TF-IDF vectorization on 50,000 IMDb reviews. • Logistic Regression achieved 88% test accuracy, outperforming oth…

    Jupyter Notebook

  3. Corporate-Data-Analyzer Corporate-Data-Analyzer Public

    A Python based desktop application that allows users to load Excel/CSV files, build group-wise reports using aggregations (Sum, Mean, Max, etc.), preview results in a table, visualize data with cha…

    Python

  4. Email-SMS-Spam-Classifier Email-SMS-Spam-Classifier Public

    • Developed an NLP-based Email/SMS Spam Detection system to identify and filter unwanted messages, achieving 97% accuracy and 94% precision using Multinomial Naive Bayes. • Compared 5 ML models and…

    Jupyter Notebook

  5. Handwritten-Digit-Recognition Handwritten-Digit-Recognition Public

    A simple Machine Learning Tkinter app that lets you draw digits and predicts them using a trained SVM model.

    Python

  6. Laptop-Price-Predictor Laptop-Price-Predictor Public

    • Built a laptop price prediction pipeline to estimate market prices based on key hardware features, comparing multiple regression models where XGBoost achieved the best performance with an R² scor…

    Jupyter Notebook