From the course: Customer Service Using AI and Machine Learning (2020)
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Evaluating success in your AI and ML projects
From the course: Customer Service Using AI and Machine Learning (2020)
Evaluating success in your AI and ML projects
- Ultimately, the success of your project will be judged by the measures it improves. So we need to talk through how we're going to measure your project. As with all technology projects, you need to track two sets of metrics. The first set let's you know how well the technology itself is working and whether people are actually using it as intended. These are leading indicators. Leading, because you only get benefits downstream if the technology is working and being used. Remember, for many projects we need training data that includes the desired answer or output as well as the input data. That way you train the algorithm both with the input and the output. Well, that's true, but there's an important detail. You don't train with all the data. Some of it you set aside to use for testing. As a general rule of thumb, you'll use 70% of your data to train your algorithm, leaving 30% to test. Sometimes you can get by with a…
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