Data Analysis and Machine Learning Projects

Welcome to my repository of Data Analysis and Machine Learning projects. Below you will find a collection of my work, categorized by their business domains for easy navigation.

Categories

1. Business Intelligence and Sales Analysis

• Maven Roasters EDA and Sales Prediction: Analysis of sales data to predict future sales trends.
• Marketing Campaigns: Analysis of customer behaviour and purchase patterns.

2. Marketing and Customer Analysis

• Red Wine Quality: Analysis of factors influencing wine quality to understand customer preferences.
• Netflix Dataset: Insights into content consumption trends to aid in content marketing strategies.
• Spotify Data Analysis: Analyzing music streaming data to understand listener preferences and behavior.
• Udemy Courses: Analysis of online course data to understand market trends in education.
• Automobile Dataset: This repository contains a Jupyter Notebook (Automobile.ipynb) that explores the Automobile dataset. The notebook covers various aspects of data analysis including data cleaning, visualization, and exploratory data analysis (EDA).

3. Risk Management and Financial Analysis

• Stocks Prices (2006-2018): Analysis of stock prices for investment risk management.
• California Housing Analysis: Predicting housing prices to aid in real estate risk assessment.
• Diamonds Dataset: Predictive modeling on diamond prices for financial decisions in the luxury market.
• Utah Real Estates: Analysis of houses and listing price prediction.

4. Public Health and Safety

• COVID-19 Analysis: Analysis of COVID-19 trends and patterns for public health policy and safety measures.
• Police Dataset: Analysis of police stops, violations, and outcomes for public safety and policy making.
• Titanic Dataset: Historical data analysis providing insights into customer segmentation and survival prediction.
• Heart Attach Prediction: Analyzing and Prediction of heart attachs from historical data.

5. Transportation and Logistics

• Flights Dataset: Analyzing flight delays and related factors for logistics and transportation management.
• Seaborn Taxis Dataset: Analysis of taxi data to understand transportation patterns.

6. Employment and Workforce

• Data Science Jobs: Preprocessing and analysis of job listings to understand market demand for data science skills and employment trends.

• Salaries Dataset: This data analysis, explores the Salary Dataset through Exploratory Data Analysis (EDA). The notebook covers various aspects of data analysis, including data cleaning, visualization, and deriving insights from the data.

Repository Structure

Each project contains:

• Data preprocessing and cleaning steps
• Exploratory data analysis (EDA)
• Model building and evaluation (for applicable projects)
• Visualization of insights

Getting Started

To get started with any of these projects, clone the repository and navigate to the specific project folder:

git clone https://github.com/mohammadreza-mohammadi94/Data_Analysis_Machine_Learning.git
cd Data_Analysis_Machine_Learning/<project-folder>

Each project folder contains a Jupyter Notebook (.ipynb) detailing the analysis and a README.md with further instructions and context.

Contributing

If you would like to contribute to this repository, please fork the project and submit a pull request.