Jan 2023 - Present
Jan 2021 - Dec 2022( 2 years )
Apr 2019 - Dec 2020( 1 year, 9 months )
Oct 2018 - Mar 2019( 6 months )
Aug 2018 - Sep 2018( 2 months )
Verify
BeautifulSoup
Scraped used and new mobile's data from 10 different websites for Egypt and Pakistan, using BeautifulSoup. Demonstrated the ability to fetch data using BeautifulSoup.
GITHUB SEARCH API • PANDAS • SEABORN • MATPLOTLIB
Fetched data for the last one million Github repositories created, using Github Search API, then analyzed the data using Pandas, Matplotlib, and Seaborn. Created multiple charts and summaries. Demonstrated the ability to fetch data using an API and perform data analysis using Python.
WEB-SCRAPING • BeautifulSoup
Developed a web scraping script to collect data from diverse online sources. The code structure, organized into the 'scraper_class,' featured nested classes and methods for efficient data extraction. Using Python librariey BeautifulSoup, I retrieved property listing data, both for buying and renting, storing it in formats such as pickle files and CSV. This project highlights my web scraping skills and proficiency in data extraction and manipulation for various online platforms.
DJANGO • REST API • PANDAS • SEABORN
Developed a comprehensive Django application encompassing extensive Exploratory Data Analysis (EDA), advanced Machine Learning (ML) models creation, and insightful market basket analysis. Leveraged strong programming skills and data science expertise to build a robust and interactive platform, enabling in-depth data exploration, accurate predictive modeling, and valuable market insights. Demonstrated ability to integrate multiple analytical techniques into a unified application, enhancing data-driven decision-making capabilities.
DATA MARTS • MYSQL • PYTHON
Designed and implemented a robust Extract, Transform, Load (ETL) script to efficiently process and integrate large volumes of data into a MySQL database. Employed manual parsing techniques and applied sophisticated logic to extract relevant information, ensuring data accuracy and consistency. Developed intricate data transformation rules and efficiently loaded the processed data into multiple tables, enabling seamless data retrieval and analysis. Demonstrated strong problem-solving skills and attention to detail in handling complex data structures and delivering a streamlined ETL workflow.
Machine Learning • REGRESSION
Developed a machine learning model to accurately predict car prices based on various factors such as brand, model, year of manufacture, mileage, and other relevant features. Gathered and preprocessed a large dataset of car listings, performed feature engineering, and applied advanced regression techniques to build a robust pricing model. Achieved high accuracy in predicting car prices, enabling informed decision-making for buyers and sellers in the automotive market. This project showcased expertise in data analysis, feature engineering, and regression modeling, highlighting the ability to deliver valuable insights and drive business outcomes in the automotive industry.
DJANGO • REST API • PYTHON • MYSQL
Developed a dynamic Django application for candidate hiring, streamlining the assessment process and enhancing the candidate experience. Implemented a secure user registration system, where candidates receive personalized login credentials via email to access the portal. Leveraged Django's flexible architecture to create a question bank with randomized selection based on the candidate's department, ensuring a tailored assessment experience. Incorporated multiple difficulty levels to accurately evaluate candidate skills and knowledge. Implemented automatic time tracking and submission features, providing a seamless assessment experience for candidates. Developed email notification functionality to inform both candidates and HR personnel of assessment completion or time expiration, facilitating efficient communication throughout the hiring process. Demonstrated strong problem-solving abilities and attention to detail in delivering a user-friendly and efficient hiring portal.
MACHINE LEARNING • PYTHON
Built a highly accurate loan default prediction model, achieving an exceptional AUC score of 0.88. Demonstrated expertise in data analysis and predictive modeling, enabling proactive customer retention strategies. Highlighted strong analytical skills and data-driven decision-making.
MYSQL • PYTHON
Conducted a comprehensive data audit, identifying and addressing multiple data inconsistencies, and errors, resulting in improved data quality, streamlined processes, and enhanced decision-making capabilities.
WEB SCRAPING • PYTHON • SQLITE
Coordinated with a highly skilled team to develop, and deploy a comprehensive suite of 200+ Python web scraping scripts. These scripts demonstrated exceptional versatility and adaptability, enabling the extraction of critical data from a wide range of websites and contributing to the team's success in project deliverables.
Machine Learning • R
Built a machine learning model to forecast customer lifetime value in the telecommunications industry. Utilized historical data and advanced techniques to accurately predict long-term customer value, enabling targeted marketing and improved customer retention. Demonstrated expertise in data analysis, predictive modeling, and driving business growth through data-driven strategies.
Machine Learning • ORACLE SQL • PYTHON
Developed and deployed a highly accurate land price prediction model using machine learning algorithms. Leveraging my expertise in data analysis, feature engineering, and predictive modeling, I created a robust solution that accurately predict land prices based on relevant factors such as location, and property attributes. This model not only provided valuable insights for real estate professionals but also contributed to informed decision-making and improved profitability in the industry.
R-shiny • Dashboard • R
Built a dashboard using R-shiny
MongoDB • Python • NLP
NLP Sentiment Analysis for TV Show Comments: Developed an NLP solution to analyze comments about TV shows and classify them as positive or negative sentiments. Demonstrated expertise in text mining, sentiment analysis, and machine learning, providing valuable insights into audience preferences and feedback in the entertainment industry.