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The project aims to study the influence of various characteristics on a person’s income. In this project, I practiced data preprocessing and visualization, and also touched on the basics of machine learning.
Machine learning algorithms are computational models that allow computers to understand patterns and forecast or make judgments based on data without the need for explicit programming. These algorithms form the foundation of modern artificial intelligence and are used in a wide range of applications, including image and speech recognition.
This program provides data loading, exploration, and analysis tools, including descriptive statistics, column categorization, target variable summaries, and correlation analysis. With error handling, it enables seamless exploration and insights extraction from datasets.
Simple Budget Tracking Analysis: SQL-based tool for personal or small business budget analysis. Track expenses, analyze income, and gain insights with SQL queries and Python.
Delve into the intricate dynamics of the Palestine-Israel conflict with my GitHub project. Using OCHA data on fatalities and injuries from 2000 to April 2024, I employ Python's powerful Matplotlib, Bokeh, and Plotly libraries to offer a comprehensive statistical analysis. Gain insights into the human toll and historical trends in the conflict.
This GitHub repository is a valuable resource for machine learning and Python enthusiasts. It includes a wide range of projects and tools, covering topics like Data Visualization, Data Analysis, ML, DL, Automation, NLP, Web Scraping, and more. Contributors are welcome to join and learn together in this supportive community. Happy coding!
The Credit Card Fraud Detection Problem includes modeling past credit card transactions with the knowledge of the ones that turned out to be a fraud. This model is then used to identify whether a new transaction is fraudulent or not. Our aim here is to detect 100% of the fraudulent transactions while minimizing the incorrect fraud classifications.