Artificial Intelligence vs. Machine Learning vs. Deep Learning

AI vs Machine Learning and Deep Learning these terms have already confused a lot of people. If you are one of them, then this blog is for you. Here in this blog, you will get to know about the terminologies of AI vs Machine Learning and Deep learning with examples. Also, you will find out how these terms differentiate from each other (Artificial Intelligence vs. Machine Learning Vs. Deep Learning) and are impacting human lives in the long run. So let’s start with an introduction. 

What is Artificial Intelligence (AI)?

Artificial Intelligence (AI) is a technology used to develop software programs competent to mimic the behavior of the human brain and carry out similar actions. And the factors that define a program as AI is a rational human-like process of making decisions and carrying out actions. Smart programs and equipment that can resolve issues in a human-like manner are the subject matter of this field. 

In this technology-driven world, AI methods are used for the prediction, automatization, and optimizations of actions earlier that were traditionally performed manually. 

The most common use of AI can be seen in face and voice recognition, speech recognition systems, translation of foreign languages and machine vision, driverless vehicles, industrial manufacturing robots, chatbots, and virtual agents. 

In addition to this, AI is majorly being used by famous brands to push personalized recommendations based on users’ searches and tastes. YouTube is one of them. At the same time, an AI-enabled inbox filtered out spam messages you received through the artificial intellect. If a car navigation system is considered, the advice you get regarding what road to take is the result of AI work. 

With all these examples of AI, you can simply understand how we are associated with AI in our daily lives and completely rely on it. 

What is Machine Learning?

Machine learning is a form of Artificial Intelligence that focuses on automatic learning and self-improvement of the system based on its past experiences, more like a human. If we talk about AI vs Machine Learning, Artificial Intelligence is an umbrella term covering all the techniques that intimidate a human brain in terms of decision making and carrying out actions. While ML majorly focuses on training the systems to comprehend unfamiliar concepts and functions and improve accordingly. 

There are three instruments of ML, which are as follows-

• Supervised learning: As the name suggests, machines are supervised by engineers to learn and get trained on labeled data in order to forecast potential outcomes. 

• Un supervised learning: In this instrument of ML, there is no need for labeled data to train the machine. On the contrary, it works to find if there is a concealed relation or pattern. This instrument is typically used by scientists when they are not aware of the specific objects of a query. 

• Reinforcement learning: This instrument of ML is used by scientists when algorithms are aimed to decide autonomously which action to prefer. This instrument helps the model learn the most effective way to react by performing several interactions with the process. This instrument can be understood as the trial-and-error approach in a more simplified form. 

• What is Deep Learning?

  Deep learning is a subset of machine learning that is mainly focused on implementing neural networks. Neural networks perform like a human brain and are competent to study provided information. They may consist of one layer to determine forecast in terms of functioning. At the same time, the availability of extra layers supports improving overall accuracy and refining the system’s functioning. 

  Thanks to deep learning, many applications get improved in terms of performance and become highly capable of calculating analytics and performing physical activities on their own. 

  Deep learning allows computers to learn in the same way as children. Like they repeat words and movements of adults to learn. 

  A driverless car, smartphones, gadgets, and IoT smart home equipment are the best examples of deep learning. 

  The deep learning models can differentiate objects based on imagery, texts, or sounds they receive. Concerning these factors, they can make decisions in the best possible way. Owing to such capabilities, systems based on deep learning can easily outperform humans in terms of speed and accuracy. 

• Source: AI vs Machine Learning and Deep Learning