AI vs Machine Learning vs Deep Learning: An Important Overview (2021)

Introduction

With the advancement in information technology, there are many misinterpretations in the meaning of certain nomenclatures. This creates misconceptions in the minds of people. On a similar footing, ai vs machine learning vs deep learning are interchangeably used. They are not one and the same but are very much similar. Broadly, artificial intelligence is on the top. Machine Learning comes under it. Lastly, Deep Learning is under machine learning. Artificial Intelligence does the task of programming systems to function as humans. Machine learning makes the systems perform their functions automatically. Deep learning is the training given to think, analyze and function as humans. So let’s take a look into each of them.

  1. What is Artificial Intelligence?
  2. What is Machine Learning?
  3. What is Deep Learning?

1. What is Artificial Intelligence?

Artificial intelligence is the intelligence shown by the systems. It is gaining popularity in today’s world. It is a combination of human intelligence that is programmed to understand human behaviour. Such systems gain knowledge with experience and perform tasks like humans. So with the growth in information technology, artificial intelligence has gained a remarkable place in our lifestyle. It is also defined as a human-created system designed to carry out tasks on its own without being escorted by humans and is widely capable of thinking and acting like humans. This is required for advanced decision making in the walks of life. It has the potential to aid humans and manage complex web problems.

Blue-chip companies have used it to streamline their business activities, improve their efficiency, automate the activities, and make predictions of the future. Artificial Intelligence helps in reducing human error, enhanced security, real-time information, a quick decision can be achieved; online assistance can be obtained and many more. It is used in healthcare, entertainment, marketing, banking and finance, manufacturing, e-commerce, human resource and many more. There has also been exponential career advancement in this field. They learn by recognizing the output patterns and compares with illustrations of the final output.

2. What is Machine Learning?

Machine Learning is a technique of analysis of data. This helps in evaluating the analytical model building. This concept comes under artificial intelligence wherein data can be evaluated, analyzed, and decision making with limited human intervention. They are not specifically programmed for such tasks, and it is because of an algorithm that all this can be possible. Systems learn all of this from the previous computations for producing the desired results. This is termed ‘training data’. Machine learning has various methods for educating the systems to accomplish certain tasks in case of no fully satisfactory algorithm available.

Machine learning in modern days has a few objectives like data classification based on the models that have been developed, future predictions based on the same and many more. It is available almost everywhere- picture recognition, audio hunt technology and much more.

3. What is Deep Learning?

Deep Learning is a division of Machine Learning which is inspired by the structure of the human brain would conclude by analyzing a vast amount of data and analyzing patterns to a perform a similar task. It basically adopts the functions of human brains. Here, deep neutral networks grasp the information, compares it with known objects and labels them into datasets into different categories by algorithms of machine learning.

A few examples to know about machine learning are the google car which can drive on its own, online recommendations from shopping apps or web series, assistants like Siri, and many more. It has evolved over the years and has bought in a magnificent amount of data from all around the world. In simpler words, deep learning can be thought of as an automatic predictive analysis. It first understands what the problem is, digs deep into the learning, later on, identifies relevant data and analyzes it, chooses the correct type of algorithm, then trains that algorithm in vast data and lastly tests the model. It uses structured as well as unstructured data for the automatic translation of relevant information.

Conclusion

From above, we conclude that artificial intelligence is the head of the family, with machine learning coming under its roof. Artificial Intelligence enables machines to carry out tasks seamlessly and intelligently. Machine learning focuses on using machines to gain knowledge by analyzing the patterns themselves. Deep learning uses algorithms to use mind working mechanisms on the basis of the human neural system. Finally, deep learning is a subset of machine learning.

Artificial Intelligence has enormous applications which are changing the world of technology widely. As days pass by, there will be more branches in this category which can outshine the current scenario to make things more commendable than ever. It is a never-ending journey of making machines intelligent. Having someone equivalent to humans used to be a dream is now slowly and gradually turning into reality to take the information technology on a high level.

There are no right or wrong ways of learning AI and ML technologies – the more, the better! These valuable resources can be the starting point for your journey on how to learn Artificial Intelligence and Machine Learning. Do pursuing AI and ML interest you? If you want to step into the world of emerging tech, you can accelerate your career with this Machine Learning And AI Courses by Jigsaw Academy.

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