CODING WITH PYTHON: THE ESSENTIAL COURSE TO MASTER IN A SMART WAY SOFTWARE CONCEPTS, TOOLS, AND ALGORITHMS FOR PRACTICAL PROGRAMMING AND DEEP MACHINE LEARNING TO BUILD ARTIFICIAL INTELLIGENT SYSTEMS by TACKE JOHN & MATTHES ADRIENNE HAWKES

Author:TACKE, JOHN & MATTHES, ADRIENNE HAWKES [TACKE, JOHN]
Language: eng
Format: epub
Published: 2020-07-27T16:00:00+00:00

Chapter 7

- Unsupervised Machine Learning

Now that we have explored a bit about supervised machine learning, it is time to explore other options that you can work with when it comes to machine learning. The first one that we spent some time talking about was supervised learning. Learning is designed in a way where you will show the computer some examples, and then you teach that computer how you would like it to respond based on the given examples. There are going to be a lot of programs where this technique is going to end up working well for you. But, when you think about showing hundreds or thousands of different examples to your computer, it is all going to seem pretty tedious. And then there are times when the program isn’t going to be able to learn this way and still give you the expected results. This is where the other two types of machine learning are going to come into play.

This is where you will find unsupervised machine learning is going to come into play. This Phase is going to spend some more time talking about unsupervised machine learning and what it is all about. Unsupervised machine learning is going to be a type of learning that is going to happen if your algorithm makes mistakes and can learn from these mistakes along the way. And the program can do it even without having an associated response to work from.

This may sound a bit confusing, but it is going to be when you can teach the computer through trial and error, without it having to work with a million examples to make sure it behaves how you would like it to do. With these different algorithms, it is possible they figure out and analyze the patterns in the data based on any provided input from you or the user.

The good news here is that there are going to be a few different algorithm types that you can work with when you decide to choose unsupervised machine learning. The algorithm that you choose to work with is going to take the data that you have, and it will restructure it so that the data can fall into one of your classes.

These classes are nice because they make it easier for you to see the information nice and sorted out, and it makes it so much easier for you to look through the information. There are many times when you will use this machine learning because it can set up your computer, or another device, to do most of the work of learning, without having a person sit there and writing out all of the instructions. The computer will do some trial and error and figure out how it should act over time.

Let’s take a look at an example. If you have a company that has a considerable amount of data that they want to read through, such as data they want to use to make predictions and make decisions about how to act in the future, and you may want to work with the machine learning.

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