Learning Types and Supervised Learning Models
Explore different learning types with a focus on supervised learning models and their role in AI product development. Learn how models like Naive Bayes, SVM, regression, decision trees, and random forests work, their uses in classification and prediction, and why continuous training is essential for accuracy.
Learning types
Again, the learning type has to do with whether or not we’re labeling the data and the method we’re using to reward the models we’ve used for good performance. The ultimate objective is to understand what kind of learning model gets the kind of performance and understandability we’re going to need when considering whether or not to use it in our product.
Supervised learning
If humans are labeling the data and the machine is looking to also correctly label current or future data points, it’s supervised learning. Because we humans know the answer the machines are trying to arrive at, we can see how off they are from finding the correct answer, and we continue this process of training the models and retraining them until we find a level of accuracy that we’re happy with.
Applications of supervised learning models include classification models that are looking to categorize data in the ...