Taimoor Mukhtar
Taimoormukhtar
Python Developer | Tableau Developer | Data Analyst
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Forecasting energy/electricity demand with XGB Regressor
This is a data science project in which an algorithm is created to distinguish dropout students from Graduate and Enrolled students. The dataset includes numerous variables that are used to train the data for student categorization. The main phases include data cleaning, exploratory data analysis, and implementing a machine learning algorithm.
The dataset includes thousands of tweets categorized by airline and sentiment (positive, neutral, or negative). Using Python-based NLP techniques, the analysis uncovers how travelers feel about different airlines and visualizes trends across platforms, routes, and experiences.
A heart disease dataset is analyzed on python using different classification methods. The main objective is to predict the heart disease using different features such as cholestrol level, age, blood presurre etc.
This is a comprehensive Data Science project in which Python is used. Two housing datasets are combined and Sale Price of houses is examined over the time alongwith the factors that affect Sale Price. The key steps of this project are Data Ingestion and Transformation, Data Cleaning, Statistical Overview and Exploratory Data Analysis.
This is a comprehensive SQL project in which the job market for data related careers are explored. Data is imported into PostgreSQL database using VScode. Data was imported from csv files (saved locally). Using the create_table operation, four different tables are created. These tables are used to carry out the analysis.
Repositories
9Forecasting energy/electricity demand with XGB Regressor
The dataset includes thousands of tweets categorized by airline and sentiment (positive, neutral, or negative). Using Python-based NLP techniques, the analysis uncovers how travelers feel about different airlines and visualizes trends across platforms, routes, and experiences.
A heart disease dataset is analyzed on python using different classification methods. The main objective is to predict the heart disease using different features such as cholestrol level, age, blood presurre etc.
This is a data science project in which an algorithm is created to distinguish dropout students from Graduate and Enrolled students. The dataset includes numerous variables that are used to train the data for student categorization. The main phases include data cleaning, exploratory data analysis, and implementing a machine learning algorithm.
This is a comprehensive Data Science project in which Python is used. Two housing datasets are combined and Sale Price of houses is examined over the time alongwith the factors that affect Sale Price. The key steps of this project are Data Ingestion and Transformation, Data Cleaning, Statistical Overview and Exploratory Data Analysis.
This is a comprehensive SQL project in which the job market for data related careers are explored. Data is imported into PostgreSQL database using VScode. Data was imported from csv files (saved locally). Using the create_table operation, four different tables are created. These tables are used to carry out the analysis.
In this project, PRAW library from python is used to extract data from 11 Reddit posts across various gaming-related subreddits. It collects post titles, authors, scores, and comments, storing the data in a CSV file for further analysis.
Propose strategies to optimize Sales and Customer Satisfaction
This project aims to import data from different sources in python and extracting insights about data quality using PANDAS library. Three different data sources are used in this dataset.