Merge pull request #105822 from nibaccam/patch-5

AutoML | Add classification + regression section

Author: PRMerger15

articles/machine-learning/concept-automated-ml.md

@@ -9,7 +9,7 @@ ms.topic: conceptual
 ms.reviewer: jmartens
 author: cartacioS
 ms.author: sacartac
-ms.date: 11/04/2019
+ms.date: 02/28/2020
 ---
 
 # What is automated machine learning?
@@ -151,6 +151,14 @@ When comparing models **A** and **B**, model **A** is a better model because it
 
 Model **C** represents a clear case of over-fitting; the training accuracy is very high but the test accuracy isn't anywhere near as high. This distinction is subjective, but comes from knowledge of your problem and data, and what magnitudes of error are acceptable. 
 
+## Classification & regression
+
+Classification and regression are the most common types of machine learning tasks. Both are types of supervised learning in which models learn using training data, and apply those learnings to new data. Azure Machine Learning offers featurizations specifically for these tasks, such as deep neural network text featurizers for classification. Learn more about [featurization options](how-to-create-portal-experiments.md#featurization). 
+
+The main goal of classification models is to predict which categories new data will fall into based on learnings from its training data. Common classification examples include fraud detection, handwriting recognition, and object detection.  Learn more and see an example of [classification with automated machine learning](tutorial-train-models-with-aml.md).
+
+Different from classification where predicted output values are categorical, regression models predict numerical output values based on independent predictors. In regression, the objective is to help establish the relationship among those independent predictor variables by estimating how one variable impacts the others. For example, automobile price based on features like, gas mileage, safety rating, etc. Learn more and see an example of [regression with automated machine learning](tutorial-auto-train-models.md).
+
 ## Time-series forecasting
 
 Building forecasts is an integral part of any business, whether it’s revenue, inventory, sales, or customer demand. You can use automated ML to combine techniques and approaches and get a recommended, high-quality time-series forecast.