December 28, 2018

In the world of modern technology, it is vital to be aware of all innovations. Each invention always precedes something great ahead. Artificial intelligence is not an exception, it was the huge stepping stone followed by the number of developments. AI consists of algorithms responsible for making a decision or a prediction about the next required tasks. The data is analyzed by those algorithms, and as a result, it is represented by the proper and quick decisions.

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Nowadays it is something that the IT services will not exist without. It is widely used in customer services for increasing its productivity and handling self-service. It has become so popular in a lot of spheres of business. Not only AI but also models of machine learning and deep learning are incorporated for the advanced applications to assist their customer with the high-quality service. You definitely faced the usage of AI, machine learning and deep learning in your everyday life. They are used for providing the best machine assistance for human beings. Remind the situations when YouTube suggests the next video to watch, or Facebook suggested you to mark some of your friends who were on the photo you’ve just uploaded. In this article, we will explain what is the difference between machine learning and deep learning, their usage, features, capabilities and how it’s related to AI.

DEEP LEARNING AND MACHINE LEARNING: EXPLAINING THE TERMINOLOGY

What do we mean under the term AI today

It is known that Artificial Intelligence is the set of algorithms that include just code and math and their task is to make the decision concerning the data. All of us understand that the development of AI didn’t stop in one place, but constantly evolving. Today we can even talk about different types of AI because the machine learning and deep learning are basically the advanced types of AI. So AI is the general term that can be used for any program that can perform smartly. Whereas machine learning and deep learning are results of AI development and adding more features and tasks. Actually, machine learning is the type of AI and deep learning is the type of machine learning. Both of them can be considered as an AI but characterized by different features, various tasks, and the number of advantages.

deep learning vs machine learning - IA structure schema

What is machine learning

First, let’s concentrate on how it generally works. Machine learning is responsible for making the decisions, but algorithms not only analyze the data, what’s more, they learn from this data and use the conclusions for future actions. The more its doing that, the better it becomes in its tasks. But only in the particular set of tasks. It doesn’t recognize the context and the abstractions. It is still more like a robot, but a very smart robot that can learn to do its job better and faster with the time. However, without going beyond its functions. Machine learning differs by the ability to adjust its actions within the certain limit of functions when it is disclosed to another data. As an advanced type of AI, machine learning is effective on its own and it does not always demand the interference of the human expert to deal with particular changes, however, it is needed to be “told” whether its predictions were true or false. This gives the possibility not to rely only on the commands of experts for each small adjustment. The computer program learns from its own experience of certain tasks and their performance and later improves based on this experience.

For example, if we set some function for the program, giving the required data, it will perform it with the progress of it. Let’s find out how it works, as for the illustration we can take music streaming services. We always wonder how our favorite songs or artists are happened to be recommended for us, actually, these are machine learning algorithms combine our preferences with the playlist of people who listens to similar music. If we compare deep learning and machine learning in this context, ML is capable of suggesting you the music you’re most likely to enjoy, but within your know preferences like genre, bands, instruments etc. On the other hand, deep learning is capable of recommending you the music you might like, but from the different genre, which is a huge step forward. But, we’ll talk about that a bit later.

So, machine learning performs various automated assignments and broadly used in numerous industries, usually proving customer services. Thus machine learning has recommended itself as the personal assistant for a lot of users.

What is deep learning

As mentioned above deep learning is the advanced type of machine learning, whereas functioning is very similar, but the capability of deep learning is quite different. Nevertheless, machine learning constantly progresses, this model still needs human assistance. It provides the prediction, later the expert makes the required adaptations. Deep learning algorithms have the ability to detect the predictions are right or wrong on its own. In this case, we can say it is capable of making logical conclusions like human beings by applying the artificial neural network. It is a layered algorithm architecture which works similarly to the human brain, therefore it has the biggest number of capabilities. On the one hand, it is the complicated task to make sure that deep learning model (sometimes called the neural model) always chooses the correct predictions. On the other hand, when it succeeds, it is a kind of scientific miracle.

For instance, the machine learning-based AI for computer board game can only make moves that it has “seen” before, but combining moves in new or the most efficient manner. Deep learning AI emulates intuition as well as quick-witted intellect, makes not unpredictable or completely new moves, thus become the winner and also the best player. It goes without saying, those capabilities are the advantages of modern technologies, it can provide unexpected results of usage in different spheres, like education, medicine, business, etc. It is the future of machine abilities.

DEEP LEARNING VS MACHINE LEARNING: THE CONFUSION

As a matter of fact, both machine and deep learning are the types of AI. A number of times people think that deep learning and machine learning are different or separate. This confusion can be easily eliminated when we remember a few facts:

Firstly, the algorithms of machine learning examine the data, learn to make a decision due to the knowledge they have obtained, despite the fact they still need the assistance of the human specialists.

Secondly, the algorithms of deep learning operate in a similar way, also learn from the given data, although these algorithms are organized in layers and capable of making own rational decision without human assistance. In deep learning, we deal with the creation of neural networks, where the work patterns of the human brain are applied for machines.

Thirdly, deep learning is the type of machine learning, whereas its algorithms have established a lot of the records in own decision making and characterized by different capabilities. Deep learning is the most powerful AI, that even can overcome own achievements in the future.

Thus, those two are not able to be separated or said to be opposite. Without hesitation, we can consider deep learning as machine learning, but simply capable of defining whether its predictions and conclusions were right or wrong without human assistance and adjust its own way of “thinking” and behavior accordingly.

DEEP LEARNING VS MACHINE LEARNING: THE DIFFERENCE

What is the difference between deep learning and machine learning? We could find it out if we realize their working structures and advantages they provide for their users. Deep learning could be mentioned through neural networks, because of the number of own accurate decisions for various tasks, like prediction, recognition, assistance, recommendation, etc. These neural networks consist of multiple layers, which have the special features of recombining learning from one layer to another. Consequently, neural networks have more chances to provide more complex features and train more intensively. And as a result of the capabilities of deep learning constantly improve over time without special programming or direct assistance. The main requirements are the training time and performance of machine approach tasks.

deep learning vs machine learning - machine learning scheme

In a nutshell, we concentrate on machine learning vs neural networks to find the difference. Their functioning is quite similar, but the difference is in final capabilities. Machine learning is able to make the conclusion from the learned data but with the certain help of the human specialist. But it is still the performance of the machine using the algorithms and the assistance of human being. Machine learning predicts the results, the professional task of the human experts will be clarifying and helping them to perform more accurately. Anyway, it is the optimization of machine performance and qualitative operations.

Netflix is one of the examples of the machine learning applying. Suggesting the next show or movie to watch, the algorithms analyze previous choices of you as well as preferences of users with similar tastes. They make the suggestion of taking into account the reactions of the user and succeed in implementing smart entertainment. Regarding deep learning the process of making conclusions goes much more further. Its algorithms act similarly to the human brain performance with the main task to reflect all activities. The structure of deep learning provides the chance to analyze a big amount of the data while being educated by it for the performance of the various tasks. The main achievement of the machines is the decomposition of the data and task assignments. Both types of learning analyze the data and learn from it, but only deep learning tries to copy the activities of the human brain when it has to make the conclusion. It is all about the real independence of the machines.

For instance, AlphaGo DeepMind is Google’s deep learning AI created to play, learn and finally beat human players in the Go board game, that is considered to be way more difficult for computers than the regular chess for example. This program really succeeded in playing, what’s more, gained the great experience from playing with the professionals, made the moves without any assistance and started to play at the unexpected level, and became itself even one of the best players of this game. So we can say that deep learning is not something that human experts are able to guarantee or even predict. It just a matter of time to find out what are its possible capabilities.

CONCLUSION

We live in the age of high technologies, where all types of inventions are characterized by a great number of incredible features and new possibilities for machine development. Today we have discussed deep learning vs machine learning. Both of them are the special algorithms that can perform certain tasks, distinguished by own advantages. It is all started from AI and developing of its capabilities. AI is the algorithms that can make a decision or prediction of the next task. If we consider machine learning it is a type of AI, where algorithms are capable of analyzing and learning from the provided data, and ready to make a final decision with little but still help of the human assistant. Thanks to constant development, we can talk about deep learning as a type of machine learning, which is identified by self-sufficient decision making which has opened wider use and keep on learning, developing and succeeding in various tasks. These are the high-tech capabilities, new advantages and tech innovations that can happen at any time: tomorrow, over the coming weeks or years. But for sure it uncovers big possibilities for both machines and human beings.

We hope that this article helped you to understand what exactly are machine learning and deep learning, find the difference between them.

Now, when you have learned the basics of those technologies, it’s time to think about how they can improve your software product or help your business. If you’re looking for the professional software development company capable of finding the best way those technologies can be leveraged for your business case and implementing it, you can reach us out at our contact page or start the dialogue in the chat widget on the right. Existek is a software house with extensive experience of AI implementation and we’ll be happy to consult you and assist in the development.