Introduction to Deep Learning

 

In past centuries, if someone told you that a machine can behave like you and perform your tasks, you would probably laugh at this absurd statement. However, today people use this technology in many aspects of their lives. We now know this technology as deep learning.

In this article, you will learn all you need about deep learning, how it works, the difference between deep learning and machine learning, its application, and lastly careers in deep learning.

What is Deep Learning?

Deep learning is the subdiscipline of the extensive field of machine learning. This technology imitates the way the human brain functions. It acts, learns, and makes decisions similar to an actual person but with higher accuracy. It does so with the help of artificial neural networks.

Artificial neural networks take the role of neurons of a brain. That is why some also call them artificial neurons. It has several layers, each performing complex action. It has nodes and neurons to perform input and output operations.

How Does Deep Learning Work?

To know how machine learning works, just picture an animal brain at its work. What do you see? Probably billions of neurons send and receive signals to perform each task. A brain has billions of neurons that work tirelessly to send and receive information and to make decisions.

In a similar way, artificial intelligence has nodes in place of neurons. These nodes are interconnected and form three layers.

·       Input Layer

The first layer is the input layer. It functions as the name suggests. It receives data and then decides what to do with this information.

·       Hidden Layer

The next layers are the hidden layer. These perform the principal functions of deep learning and thus are several in number. This layer receives all the necessary information from the input layer. It then performs complex mathematical operations on it. It performs all the learning, image processing, facial recognition, and other similar tasks.

·       Output Layer

The hidden layer converts the data into output. It sends it to the output layer. The output layer is the last layer of the artificial neural network. It provides the answer to your questions in addition to making predictions.

Difference between Deep Learning and Machine Learning

As established above, deep learning is the subfield of machine learning. Now, let's learn what is the difference between these two fields. Before that, let us first revisit the concept of machine learning.

Machine learning deals with computers and their algorithms. Its main function is to help the computer learn from a specific set of data. The computer then performs tasks and makes decisions based on this analysis. All that is done without any use of complex programming methods.

On the other hand, deep learning does not work in a machine-like manner, unlike machine learning. It performs more sophisticated human-like functions.

Deep learning and machine learning has the following key differences:

1.     Human Supervision

Machine learning is usually unable to provide the end results on its own. It requires regular human intervention in order to do so.

Whereas, deep learning does not need that much supervision to perform its tasks.

2.     Efficiency

Deep learning provides more efficient results but it takes more time to operate.

On the other hand, machine learning needs less time to operate but the results will not be that productive.

3.     Data Processing

Deep learning and machine learning are also dissimilar in the way they take and process data. Machine learning uses long-established operations to process structured data. Whereas, deep learning uses artificial neural networks to process even unstructured data.

Applications of Deep Learning

Artificial Intelligence and deep learning are all the rage these days. Whether you are aware of it or not, the deep learning technology has already found its use in multiple devices you own.

Here we have listed some of the most common applications of deep learning:

·       Automated Cars

Out on the roads, you may have seen at least a few self-driving cars. Ever wondered how they work? An automated vehicle is a concept that has been made possible with the help of deep learning.

It is also used in automobile industries to improve safety measures.

·       Healthcare Facilities

This technology has far greater precision than a human. That is why healthcare facilities have started using this innovation. Cancer detection is a difficult task. But with the help of deep learning, it has become easier than ever.

·       Online Shopping

You may get surprised sometimes when you see an advertisement for something you need on your home page. Or when a website starts providing personalized recommendations for you. These e-commerce platforms also use deep learning to increase sales.

·       Home Assistant

You can find deep learning in electronic devices such as translation devices or home assistants. Call out to your home assistance device and it will respond and assist you.

·       Safeguarding

Deep learning can be of great help in war-like situations. It will recognize the danger in any area and help evacuate people.

It can also predict risky situations such as earthquakes.

Careers in Deep Learning

Undeniably, deep learning is a very interesting field with a vast set of applications. If you are interested in computer software, problem-solving, and artificial intelligence, then this might be the right field of study for you.

After learning about this technology, you can go for various career paths. We have listed some of them below:

1.    Data Engineer

It is a field that uses all kinds of science including biomedical science. You will also need the knowledge of programming languages to excel in this field. Data engineers build programs to collect data and interpret it.

2.     College Professor

If you want to go for the teaching profession, you can choose to pursue a Ph.D. degree in this field. This way you will easily find a job as a college instructor.

Deep learning is a field that will have a great impact on future generations. That is why it needs talented people to make progress and change peoples’ lives.