Employee Attrition Prediction using machine learning

Attrition is the silent killer that can switly disable even the most successful and stable of the organizations in a shockingly spare amount of time. Hiring new employees are extremely complex task that requires capital, time and skills.Also new employee costs a lot more than that Persons salary.

• The cost of hiring an employee goes far beyond just paying for their salary to encompass recruiting, training, benefits, and more.
• Small companies spent, on average, more than $1,500 on training, per employee, in 2019.
• Integrating a new employee into the organization can also require time and expenditures.
• It can take up to six months or more for a company to break even on its investment in a new hire.

The Cost of Hiring a New Employee - Investopedia

In this project, I have developed a Machine Learning Model to predict the Employee Attrition by implementing various Machine Learning Algorithms. Conducted exploratory data analysis using various data visualization techniques.

Achieved good accuracy on the 'IBM HR Analytics Employee Attrition & Performance' dataset from Kaggle,using Logistic Regression.

Algorithm :

1. *Logistic Regression* is used for development of model.

Technology Used

1. Python
2. Machine Learning
3. Pandas
4. Numpy
5. Scikit-learn
6. Flask
7. HTML
8. CSS

Installation Step : -

1. Python 3.7.0
2. command 1 - python -m pip install –-user -r requirements.txt
3. command 2 - python app.py

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