Machine Learning Introduction

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[When we are looking through the field of information technology and some of the different things that you are able to do with that, you will find that machine learning is definitely a big part of that. It is possible that, depending on your area of expertise, you have not heard much about machine learning, but there is so much that you are able to do with this field, and with the programming that comes with machine learning and it won’t take long before this field is going to grow like crazy. In this post we will take you through machine learning introduction...

A good example of machine learning that you have been using already, without even realizing it, is when you use any kind of search engine, whether it is Yahoo!, Google, or Bing. Any time that you are looking up some information and doing a search query. Machine learning is the primary programming thing that is behind it and can help the search engine do the work that you want. The program can use the idea of machine learning in order to help you find the right answers and results that you want.

Machine Learning Introduction

Of course, this is just going to be one example of the different technologies that are going to use machine learning. You will find that other applications, including spam messages and avoiding those, can rely on machine learning and computer learning along the way. Unlike what we are able to see with some conventional programs that have been done, and the other programming techniques that you may have used, machine learning programs are unique because they are able to adapt and even learn the behaviors that the user likes to rely on, and then makes predictions and gives answers like that. This will make them more versatile, helps them to get smarter and stronger, and will make it easier to get some of the results that you are looking for.

If you are working with some program that already has the supervised machine learning technology on it, then you will be able to train your computer how to learn from any input that a potential user is going to provide to it. And you do not have to do this by thinking up every possible outcome and input from the beginning.

Machine learning will take over and can provide the computer and technology with the right answers, even if the problem is considered a bit more complex. The input for this learning process, which we call the learning algorithm in machine learning, is going to be used in data training. We will take a look at some of the different learning algorithms that show up in machine learning along the way in this guide.

Machine Learning Introduction: So, what is machine learning?

Now that we have that little introduction, it is time to get into some more details about what this machine learning process is all about. This is basically a new type of programming, or newer compared to some of the other programming options that we have seen in the past, that will focus on helping the computer learn and get smarter, without the programmer having to go in and figure out all of the results and all of the answers ahead of time. This allows the program or the technology to do a lot of things that it wouldn’t have been able to do in the past.

With machine learning, you are teaching the computer or the program to use its own experiences with the user in the past in order to perform better in the future. An example of this would be a program that can help with spam email filtering. There are a few methods that can work in this instance, but the easiest one would be to teach the computer how to categorize, memorize, and then identify all the emails in your inbox that you label as spam when they enter your email. Then, if some new emails come in later that match what is already on your email list, the program would be able to mark these as spam without any work on your part.

While this kind of memorization method is the most straightforward technique to program and work with, there are still some things that will be lacking with it. First of all, you are missing out on the inductive reasoning in the program, which needs to be there for efficient learning. As a programmer, it is much better to go through and program the computer so that it can learn how to discern the message types that come in and that are spam, rather than trying to get the program to memorize the information.

Let us see if we can keep this process a bit easier to understand, so we see how unsupervised machine learning works without being confused. Let us say that you are working on a program so that the computer can scan any of the emails that are already known as spam and found in your spam folder. From this scan, the program is then able to recognize when a new piece of mail comes in and is spam, looking at the words and the phrases that appear and are common in other spam messages. If the program were done correctly, it would be able to catch most of the spam that is coming your way, place it in the spam folder, and you would never see them unless you actively went and looked.

This method is often seen as one of the best ones to use, but you have to use a bit of caution with it. You need to pay attention to what the machine learning algorithm is doing, and you need to realize that as a program, the computer could get it wrong sometimes. This is not as big of a deal when it comes to spam because you may miss out on a few emails that were classified as spam and weren’t really a problem, and a few spam messages may get through to your regular email. These aren’t that big of a deal, but if you are not watching and teaching the program with machine learning along the way, then bigger mistakes with other problems can come up.

Are there any benefits to using machine learning?

With that basic understanding of machine learning, it is time to figure out why someone, especially a programmer, would want to take a look at machine learning and actually use it for their needs. There are a lot of problems and complex pieces of code that machine learning can help you out with, but we are going to put most of our focus on the main two reasons and methods that cause programmers to go with machine learning.

The first one is that programmers are going to use the basics of machine learning to help them with any complex coding task so that the programmer can make it easier and add it to the computer or another piece of technology. And the second one is how machine learning can help with any of the tasks that are adaptively generated. With this in mind, let us take a look at some of the times when you would meet one of the criteria above and find that machine learning is the best option for you.

Complicated tasks

One way that you can use machine learning is to help with some programming tasks that are complicated. There will be some tasks that you can work on in programming that may not respond that well to conventional programming. These tasks may not have the right amount of clarity that you need to use a conventional program, or they just have too much complexity with them.

The first set would be the tasks that people and animals can perform. Think about speech recognition, image recognition, and driving as examples of these. Humans can do these just fine, but if you used conventional programming tools to teach the computer how to do this, it is going to run into trouble. it is much better for the computer to learn the right way to do these tasks by receiving good outputs when they are right. Machine learning can help make this happen.

The second issue is that machine learning can help with tasks that are too hard for humans to do. These would include things such as going through a complex analysis where there is too much data for one person to go through well. Companies may decide to use machine learning when they wish to go through a ton of data science workflow and make decisions and predictions.

In addition to that, you will find that machine learning can be used in other similar manners to help with processes like weather predictions, search engines, and even genomic data. There is going to be a lot of information that is valuable in all of the sets of data that you get. But it would take a lot of time, and many people, to have the energy and the time to go through this information. It would take too long, and the information would be dated and useless by the time they did, and mistakes would be made. Machine learning can step in here and do the work in a fraction of the time, providing you with predictions and more to make based on that information.

While you are able to do a ton of neat things when using the traditional programming forms, and these traditional coding methods have worked for a long time to help programmers actually get things done that they need, there are a lot of tasks in our growing field of technology that just is not going to get the help they need from these older methods. This is why machine learning is so valuable. It is going to fill in some of the gaps along the way while still giving you the results and the information that you need.

Adaptively generated tasks

Another thing to look at is how machine learning is going to help with some of the adaptively generated tasks. You may find that there are a ton of things that conventional coding can do, but there are also some limitations. One of these limitations that can cause problems is how the traditional programs are a bit rigid. Once you write out the code and start to let it implement, the codes are going to stay the same without any learning or growing along the way. The code is going just to do the same thing over and over again unless someone goes in and makes some changes. It won’t learn and adapt. For some programs, this is just fine and exactly what the programmer wants, but for others, it places some limitations.

You may work on some program where you want it to learn or adapt, or you would like it to have the capability of reacting to any kind of input that it will receive. This is not something that the conventional program can do at all, but you can bring in some of the ideas that come with machine learning to make it happen.

Easy to work with

While there are some tasks and algorithms that we will talk about later on may seem complicated, they are really neat examples of what you can do with machine learning. These tasks are complicated with conventional programming, but this is where machine learning will come into play. Things like speech recognition and facial recognition may be hard to do with conventional programming, but with machine learning, you can get it done in no time.

Machine learning is a great program to work with because it has the ability to learn as it goes along. Let us take a look at speech recognition. The program may start out having trouble with understanding the user when it first starts. You may find that you need to repeat the word a few times to get the program to work and understand you.

But as you keep using it, the program is going to start recognizing what you are saying. It will know your accent and the ways that you say some words that may be different than the way others say about it. The program can even get better at making predictions that are right for you and providing answers for the user the longer that the program is used.

The program that we are looking at here is going to be able to do this learning, no matter what device it is being used on. This makes sure that you are able to get the program to speak. When it comes to using some of the traditional or conventional methods of programming, this is hard to do. The coding language is not going to be set up to learn how people speak, and you will be left with something that does not work. But machine learning can listen to the speech patterns of another person and adapts until it is able to recognize and follow what the other person is saying.

While you may be a bit worried reading about machine learning because it seems like there are just so many different things that it is able to help out with, you will be surprised to find that it is actually really easy to work with. If you have already had a chance to work with some of the programming languages in the past, especially with Python, then you will find that it is easier to work with this machine learning coding as well. And since there are a lot of options that you can choose including reinforcement learning, unsupervised learning, and supervised learning, so you are sure to be able to design the kind of program that you need with this.

Machine Learning Introduction: The applications you can use with machine learning

As we go through some of the different parts of machine learning and start working with some of the algorithms that come with it, you may notice that there are a ton of things and applications that will work with this. And there really is no limitation when it comes to how you can use this machine learning because it is growing and changing all of the time. More and more programmers are learning how to use this kind of programming method and finding new ways to make it work for them. Some of the best methods of using the learning algorithms that go with machine learning today include:

Statistical research: machine learning is a big part of IT now. You will find that machine learning will help you to go through a lot of complexity when looking through large data patterns. Some of the options that will use statistical research include search engines, credit cards, and filtering spam messages.

Big data analysis: many companies need to be able to get through a lot of data in a short amount of time. They use this data to recognize how their customers spend money and even to make decisions and predictions about the future. This used to take a long time to have someone sit through and look at the data, but now, machine learning can do the process faster and much more efficiently. Options like election campaigns, medical fields, and retail stores have used machine learning for this purpose.

Finances: some finance companies have also used machine learning. Stock trading online has seen a rise in the use of machine learning to help make efficient and safe decisions, and so much more.

As we mentioned above, there are just a handful of the methods that can utilize all of the neat features that come with machine learning, and the different ways that you are able to use machine learning in your business. But the possibilities of what you are able to do with this machine learning, and how this can help your business to grow are limitless, and a lot of the different machine learning algorithms that we will talk about in this guide will help you to see all of the great possibilities.

What are some of the things where we can use machine learning?

You will find that there are already a ton of different things that we are able to use machine learning for, and the list is just going to keep growing over time. Machine learning is definitely a great tool that a lot of programmers and companies are exploring because it opens up a ton of options for what they can do with programming and more, especially when it is compared to traditional forms of coding. Some of the challenges that you can use machine learning to help out with include:

Creating a search engine. Search engines are going to rely heavily on the learning capabilities of machine learning. A search engine is able to learn from some of the results that it gets when you do a search query. The first few times that you use a new search engine, it may be a little less accurate, and you may not want one of the results that first comes up. But the more that you use the search engine, the better it can learn and will figure out what you want it to find for you each time you use it.

Collaborative filtering. This is one of those challenges that any retailer online is going to run into because when it is used correctly, it is going to help you to get more profits through sales. Think about the last time that you were on a site like Amazon. After you have been able to do a few searches, you are going to start noticing that the site gives you recommendations on what you should choose next to purchased, based off the past purchases you have done. This is all done with the help of machine learning because it has to learn what you did in the past and match it up with some of the things that you may try to do in the future. If it is right, then the store can make more money from the same person.

Automatic translation is the next option on the list. If you are doing any kind of programming work where you need things to be translated, then this is an excellent example of machine learning. Your program has to be able to take a look at the document presented, and then understand and recognize the words that are there. There also has to be some learning of the context, syntax, and grammar of the words as well.

This is even more complicated when you think about any mistakes that may show up in the original document. This is going to make it harder for the program actually to learn what it is supposed to do. With the help of machine learning though, the program is able to learn how to translate a language from one to another, and can even do it with more than two languages at a time. The programs that are out to help us get this done are still in the beginning stages, and it may take some time before we really see it take off, but it is still a cool technology to work with.

Name recognition can be done with machine learning, as well. This is going to happen when a program is able to look through some document and identify different entities such as actions, names, places, and titles. This can be done any time that you are working with a kind of program that is supposed to digest and then comprehends the document that is handed to it.

For this one, let us say that you are working with one of the many email servers out there, including Gmail. Some of these are going to be sent out to a new customer and will provide them with the ability to see a brand-new email address as soon as it comes into the inbox. It is also set up to automatically take that information and add it into the address book so that the information is ready for you when you need it, saving time and effort in the process.

Speech recognition is definitely changing the way that technology works when it comes to machine learning. This is a challenge for any kind of programming needs because there are so many languages, dialects, and individual speech patterns that the technology has to memorize. But a good example of this would be some of the products that Amazon has released, such as the Amazon Echo. You may see that this technology makes some mistakes in the beginning as it learns. But once it gets used to the speech patterns of the individual and what they are saying, it is going to start getting the results done in no time.

And then there is facial recognition. Machine learning is able to help us with this challenge, as well. This kind of challenge is unique because the system has to be able to work through many different layers in order to see if it recognizes a face or not. This type of machine learning is going to rely on images including videos and pictures so that only the people who are approved and who hold onto the right authorization would be able to use this kind of system.

Through a variety of different learning processes that are available, the program, when it is set up properly with machine learning, will then be able to look at a face and determine if that person is allowed or not. If this one is used with traditional programming, or not set up correctly, then it is possible that the wrong people are going to get onto the system and this can cause issues with security and more.

As you can see, there are already a lot of different uses out there when it comes to utilizing the learning capabilities that come with machine learning. This type of programming is able to step in and help a programmer get through some complex technical issues, ones that conventional programming just may not be able to handle. Many of the topics and the algorithms that we are going to discuss in this guide will help us to see just how much the process of machine learning is able to do to help with this.

Types of machine learning

We are going to discuss these in more detail as we go through the next few chapters in this guide, but you will find that there are generally three types of machine learning that you can work with, and the different algorithms that you choose from when doing a machine learning project will fall into one of these three categories.

First, we are going to have supervised machine learning. This is seen as one of the basic forms of machine learning, and it is going to require the most work from the programmer. With this method, we are going to see that the programmer is going to have to show a lot of different examples to the machine so that it can learn what it is supposed to do. Over time, the machine is going to be able to compare future examples to the ones that it was taught in the beginning, and can make accurate predictions, but only if the programmer showed enough examples and showed examples that were accurate in the first place.

From there, we are able to move on to unsupervised machine learning. This one is going to take things to the next level and helps the machine to learn, without all of the examples given by the programmer. This one takes a bit more work to program, but the machine is going to be able to learn from the results that it gets from the user, determining what the right output would be over time. It may be a little inaccurate in the beginning as it is learning, but as time goes on, this machine is going to be able to make accurate predictions and give the right output based on the person who is using it.

And the third type of machine learning is going to be the reinforcement learning. This kind of learning is similar to unsupervised machine learning in that it is going to focus on the feedback from the user in order to figure out if the output it provides is accurate or not. But this one is going to be based more on a true or false kind of idea instead. If the answer that it provides is true, it is going to be rewarded for that, which allows it to keep that information stored and ensures that it will be more accurate with time.

The different algorithms that we will discuss in a few chapters will all fit under the category of supervised machine learning, unsupervised machine learning, and reinforcement machine learning, and each of them can be brought out for different things based on the kind of program that you are going to work with.

A bit about deep learning.

The next thing that we need to focus on for a moment to help us out with machine learning, and which goes along with this kind of thought and with what is data science, that we talked about before is the idea of deep learning. This is going to be a subfield of machine learning involving algorithms that are inspired by the function and structure of the brain known as artificial neural networks. It is going to work to teach your computer to act and behave the way that a natural to humans, that is, that the system will be able to learn by example.

It is through the help of this kind of deep learning that your computer is going to be able to learn to perform the various classification tasks directly from sound, image, and text. Deep learning models are able to achieve the state-of-the-art accuracy, which in some cases will be able to exceed the performance that you can get at the human level. Large sets of labeled data and neural network architectures are going to be used to train models with some deep learning.

As you can see, there are a lot of different parts that can come with machine learning. It is a great tool that you can use in order to get your computer or your system to do some of the things that you may struggle with. For example, machine learning can be used in order to help work with search engines, and maybe with providing you with some recommendations when you are shopping online. Even if you need to sort through a large amount of data, machine learning can come into play and help out.

As you can see, there are a lot of different parts that can come together when we are working with machine learning. We will take a look at some of the different options that you can explore with the types of machine learning that you want to do later on, but overall, machine learning can bring your programming to the next level, especially when you use it in components of data science and big data like we will talk about later. [what is big data?]