Skip to content
View shadalishah's full-sized avatar
  • Islamabad, Pakistan

Block or report shadalishah

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don't include any personal information such as legal names or email addresses. Markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse

Popular repositories Loading

  1. Applied_solutions_of_ISLP Applied_solutions_of_ISLP Public

    This repository contains solutions for the exercises from "An Introduction to Statistical Learning with Applications in Python" by Tibshirani et al., 2023 edition.

    Jupyter Notebook

  2. Merge_multiple_files_into_a_single_file_using_python Merge_multiple_files_into_a_single_file_using_python Public

    This dataset contains information on global happiness collected annually from 2015 to 2024. The data is sourced from the World Happiness Report and provides a comprehensive view of the factors infl…

    Jupyter Notebook

  3. Modeling-Pakistan-Macroeconomic-Dynamics-A-Time-Series-Approach-Using-VAR-SVAR-and-VECM Modeling-Pakistan-Macroeconomic-Dynamics-A-Time-Series-Approach-Using-VAR-SVAR-and-VECM Public

    This repository presents an applied macroeconometric analysis of Pakistan’s economy using modern time series techniques, including Vector Autoregression (VAR), Structural VAR (SVAR), and Vector Err…

  4. house-price-prediction-kaggle house-price-prediction-kaggle Public

    Predicting residential house prices using ML models (XGBoost, Random Forest, Linear Regression) on Kaggle Ames Housing dataset. Public Score: 0.13253

    Jupyter Notebook

  5. UAE-Real-Estate-Price-Prediction UAE-Real-Estate-Price-Prediction Public

    Machine learning project predicting UAE property prices using 41K+ Bayut.com listings. Includes EDA, preprocessing, and Random Forest model achieving 95.6% accuracy (R²=0.9564) with 12.13% average …

    Jupyter Notebook

  6. churn-ml-causal-business-insights churn-ml-causal-business-insights Public

    End-to-end Customer Churn Prediction using Machine Learning & Causal AI | Gradient Boosting | EconML | Business Impact Analysis | Python

    Jupyter Notebook