In this project, you will play detective, and put your machine learning skills to use by building an algorithm to identify Enron Employees who may have committed fraud based on the public Enron financial and email dataset.
Prepare for this project with: Intro to Machine Learning.
If you have successfully completed the project for the Intro to Machine Learning course in the past (which entails having graduated from the course and having access to your course certificate), simply email us at dataanalyst-project@udacity.com with your passing evaluation and we'll give you credit for this project.
This project will teach you the end-to-end process of investigating data through a machine learning lens.
It will teach you how to extract and identify useful features that best represent your data, a few of the most commonly used machine learning algorithms today, and how to evaluate the performance of your machine learning algorithms.
By the end of the project, you will be able to:
- Deal with an imperfect, real-world dataset
- Validate a machine learning result using test data
- Evaluate a machine learning result using quantitative metrics
- Create, select and transform features
- Compare the performance of machine learning algorithms
- Tune machine learning algorithms for maximum performance
- Communicate your machine learning algorithm results clearly
Machine learning is a first-class ticket to the most exciting careers in data analysis today.
As data sources proliferate along with the computing power to process them, going straight to the data is one of the most straightforward ways to quickly gain insights and make predictions.
Machine learning brings together computer science and statistics to harness that predictive power.