This repository contains a collection of data analysis projects that I have worked on.
The projects are organized into the following categories:
Exploratory Data Analysis (EDA): These projects involve exploring a dataset to gain insights into the data. This may involve cleaning the data, identifying patterns, and generating visualizations.
Machine Learning (ML): These projects involve using machine learning algorithms to build models that can make predictions. This may involve training a model on a dataset of labeled data, evaluating the model's performance, and using the model to make predictions on new data.
Natural Language Processing (NLP): These projects involve using natural language processing (NLP) techniques to analyze text data. This may involve tokenizing text, identifying parts of speech, and generating sentiment analysis results.
Each project includes a README file that provides more information about the project, such as the data source, the data analysis techniques used, and the results of the analysis.
I hope that this repository will be a useful resource for anyone who is interested in learning about data analysis.
To get started with the projects in this repository, you will need to have the following installed:
Python 3.6 or higher A Jupyter Notebook environment Once you have installed the necessary software, you can clone the repository to your computer using the following command:
git clone https://github.com/AdadAlShabab/End-To-End-Data-Analysis-Projects.git
This will create a directory called data-analysis-projects in your current directory.
To run a project, open the Jupyter Notebook file for the project in a Jupyter Notebook environment. Once the notebook is open, you can run the cells in the notebook to execute the code.
I welcome contributions to this repository. If you would like to contribute a new project, please create a pull request.