The Goal is to predict whether a person has an income of more than 50K a year or not.
This is basically a binary classification problem where a person is classified into the
50K group or <=50K group.
Life Cycle of implementing machine learning application.
- Gathering the Data
- Data Preparation
- Data Preprocessing
- Create Model
- Evaluate Model
- Deploy the model
The UCI Adult Dataset has been used for this purpose, taken from the Kaggle. link is below.
- Python (Programming Language version 3.7+)
- Flask (Python Backend Framework)
- sklearn (Machine Learning Library)
- pandas (Python Library for Data operations)
- NumPy (Python Library for Numerical operations)
- imblearn (sampling Library)
- VS code (IDE)
- Azure (Cloud platform)
- Create virtual environment
conda create -n myenv python=3.8
- Activate the environment
conda activate myenv
- Install the packages
pip install -r requirements.txt
- Run the app
python app.py
- Navigate to URL http://127.0.0.1:5000/
- Enter valid values in all input boxes and hit Predict.
If everything goes well, you should be able to see the predcited salary Class on the HTML page!
Devansh Mistry - Linkedin