Recognizing Data Patterns

Has your engineering manager, lead, or architect ever come to you with a request similar to one of the following:

• Can we use the customer data from last year to predict which customers in the sales pipeline are likely to covert? 
• How about leveraging defect history from prior releases to estimate the health of the current release? 

In cases like these, it is assumed that:

• The problem is well-defined.
• There is data available.
• It may be possible to use ML to recognize patterns in that data.
• Leveraging such a model to make predictions could be valuable to the business.  

Your first ML project is aimed at developing the skills needed for you to deliver on such "one-off" models.  It describes a well-defined problem and available data.  You are then tasked with implementing a predictive ML model to solve the problem.

A program that outputs or displays the message "Hello, world!" is often the first a student learns to write in a given language.   Similarly, you'll start your ML journey with a simple yet end-to-end project supported by easy-to-use tools .