Adult Census Income Prediction

The Adult Census Income Prediction project is a machine learning project that predicts an individual's income level based on their demographic and socioeconomic characteristics. The goal of this project is to develop a machine learning model that can accurately predict an individual's income level, i.e., whether they make less than or equal to $50,000 per year or more than $50,000 per year.

Dataset

The project uses the Adult Census Income dataset, which contains demographic and socioeconomic characteristics of individuals, including age, education, occupation, marital status, and more. The dataset can be obtained from the UCI Machine Learning Repository or Kaggle.

Solution

The proposed solution involves building a binary classification algorithm to predict an individual's income level. The solution includes the following steps:

1. Data preprocessing
2. Feature engineering
3. Model selection
4. Model training
5. Model evaluation
6. Model deployment
7. CI/CD pipelines
8. Requirements

The project requires the following dependencies:

1. Python 3.x
2. Scikit-learn
3. Pandas
4. NumPy
5. Flask

Usage

To run the project, follow these steps:

1. Clone the repository to your local machine
2. Install the required dependencies using pip install -r requirements.txt
3. Run the main.py file to preprocess the data, engineer features, select the best model train the model, and evaluate the model on the test set.
4. Deploy the model in a production environment.

License

The project is licensed under the Apache license.

Software and account requirement:

1. Github Account
2. [Railway account]
3. VS Code IDE
4. GIT Cli

Useful Commands for extra knowledge

Create virtual environment

conda create -p venv python==3.7 -y

To activate virtuak environment

conda activate venv

or

conda activate venv/

To install all requirements from the requirements.txt file

pip install requirements.txt

To check the git status

git status

To check all version maintained by git

git log

To check the version/commit alll changes by git

git commit -m " message"

To send or push version changes to git

git push origin main

To check remote url

git remote -v

Requirements for app deployment on cloud flatform(Railway)

1. RAILWAY_TOKEN:

To build docker image

docker build -t <image_name>:<tag_name> location  # can use . as location for current location

Note : Image name should be lower case

To list docker images

docker images

To run docker image

docker run -p 5000:5000 -e PORT=5000 <image_ID>

To check running container in docker

docker ps

To stop docker container

docker stop <container_id>

To install all requirements and created packages using setup file

python setup.py install

To install ipykernal ''' pip install ipykernal '''