Difference between revisions of "Supervised"
| Line 7: | Line 7: | ||
[http://www.youtube.com/results?search_query=supervised+Machine+Learning YouTube search...] | [http://www.youtube.com/results?search_query=supervised+Machine+Learning YouTube search...] | ||
[http://www.google.com/search?q=supervised+deep+machine+learning+ML+artificial+intelligence ...Google search] | [http://www.google.com/search?q=supervised+deep+machine+learning+ML+artificial+intelligence ...Google search] | ||
| + | |||
| + | In supervised learning, you provide a training data set with answers, such as a set of pictures of animals along with the names of the animals. The goal of that training would be a model that could correctly identify a picture (of a kind of animal that was included in the training set) that it had not previously seen. [http://www.infoworld.com/article/3394399/machine-learning-algorithms-explained.html Machine learning algorithms explained | Martin Heller - InfoWorld] | ||
This kind of learning is possible when inputs and the outputs are clearly identified, and algorithms are trained using labeled examples. To understand this better, let’s consider the following example: an equipment could have data points labeled F (failed) or R (runs). [http://www.simplilearn.com/what-is-machine-learning-and-why-it-matters-article Machine Learning: What it is and Why it Matters | Priyadharshini @ simplilearn] | This kind of learning is possible when inputs and the outputs are clearly identified, and algorithms are trained using labeled examples. To understand this better, let’s consider the following example: an equipment could have data points labeled F (failed) or R (runs). [http://www.simplilearn.com/what-is-machine-learning-and-why-it-matters-article Machine Learning: What it is and Why it Matters | Priyadharshini @ simplilearn] | ||
Revision as of 06:13, 22 May 2019
YouTube search... ...Google search
In supervised learning, you provide a training data set with answers, such as a set of pictures of animals along with the names of the animals. The goal of that training would be a model that could correctly identify a picture (of a kind of animal that was included in the training set) that it had not previously seen. Machine learning algorithms explained | Martin Heller - InfoWorld
This kind of learning is possible when inputs and the outputs are clearly identified, and algorithms are trained using labeled examples. To understand this better, let’s consider the following example: an equipment could have data points labeled F (failed) or R (runs). Machine Learning: What it is and Why it Matters | Priyadharshini @ simplilearn
