- By Arya Admin
Science & Technology,
- Posted April 16, 2021
What are the popular applications for Artificial Intelligence graduates?
Most popular applications for the graduates of BTech Artificial Intelligence
Today, the resources about Artificial Intelligence (AI) are quite overwhelming. There are some basic concepts and applications that students of BTech Artificial Intelligence need to know in the field of Artificial Intelligence including the following:
1. Machine learning
Machine learning enables machines to “learn” a task from experience without programming them particularly about that task. This process starts with feeding them good quality data and then training the machines by building different models using different algorithms. The choice of algorithms is completely dependent on the kind of task individuals are trying to automate. However, Machine Learning Algorithms are basically divided into 3 types including supervised learning, unsupervised learning and reinforcement learning.
2. Deep Learning
Deep Learning is a subset of Machine Learning. It allows processing of data and creating predictions using neural networks. These neural networks are connected in a web/like structure similar to the networks in the human brain for the graduates of Top Engineering Colleges in Jaipur. This web-like structure of artificial neural networks means that they are able to process data in a non-linear approach, which is an important benefit over traditional algorithms.
Rank Brain is one of the most important factors of deep neural network in the Google Search Algorithm.
3. Reinforcement learning
Reinforcement learning is a part of Artificial Intelligence in which the machine learns something in a way that is similar to how humans learn. For instance, imagine that the machine is a student. Here the hypothetical student learns from its own mistakes over time through trial and error. In other words, the algorithm decides the next action by learning behaviors that are based on its current state and that will maximize the reward in the future.
Robotics is a field that mainly deals with creating humanoid machines that can behave like humans and perform some actions like human beings. Now, robots can act like humans in some situations and can think like humans as well. This is where artificial intelligence comes in. Al allows robots to act intelligently in certain situations with the help of the students of best engineering colleges in Jaipur. These robots may be able to solve problems in a limited sphere or even learn in controlled environments.
For instance, Kismetis a social interaction robot developed at Artificial Intelligence Lab. It recognizes the human body language and also our voice and can interact with humans accordingly. Similarly, Robonaut was developed by NASA to work alongside the astronauts in space.
5. Natural Language Processing (NLP)
Nobody denies the fact that humans can converse with each other using speech but now machines can too. This is known as Natural Language Processing where machines analyze and understand language and speech as it is spoken. There are many sub-parts of NLP that deal with language like speech recognition, natural language generation, natural language translation, etc.
NLP is currently extremely popular for customer support applications, particularly the chat bot for the students of top computer science engineering colleges in Jaipur. These chat-bots use ML and NLP to interact with the users in textual form and solve their queries. Thus, individuals get the human touch in their customer support interactions without ever directly interacting with a human. Some of the most popular examples of NLP applications are Alexa from Amazon and Siri from Apple.
6. Recommender Systems
While using Netflix, you might get a recommendation of movies and series based on your past choices or genres you like. This is done by Recommender Systems that provide you some guidance on what to choose next among the vast choices available online.
A Recommender System can be based on Content-based Recommendation or even Collaborative Filtering. Content-Based Recommendation is done by analyzing the content of various different items. For instance, students of best engineering colleges in Rajasthan can be recommended books they might like based on a description of the item and their own basic profile. On the other hand, Collaborative Filtering is done by analyzing the past reading behavior of people similar to them and then recommending books based on that.
7. Computer Vision
The internet is full of images. This is the selfie age, where taking an image and sharing it has never been easier. In fact, millions of images are uploaded and viewed every day on the internet. To make the best use of this huge number of images online, it is important that computers can see and understand images. And while humans can do this easily without a thought, it is not so easy for computers. This is where Computer Vision comes in. Computer Vision uses Artificial Intelligence to extract information from images. This information can be object detection in the image, identification of image content to group various images together, etc. An application of computer vision is navigation for autonomous vehicles by analyzing images of surroundings like AutoNav used in the Spirit and Opportunity rovers which landed on Mars.
8. Internet of Things
Artificial Intelligence deals with the creation of systems that can learn to emulate human tasks using their prior experience and without any manual intervention. On the other hand, Internet of Things or IoT is a network of various devices that are connected over the internet and they can collect and exchange data with each other.
Now, all these loT devices generate a lot of data for the students of computer science engineering colleges that needs to be collected and mined for actionable results. This is where Artificial Intelligence comes into the picture. It is mainly used to collect and handle the huge amount of data that is required by the Artificial Intelligence algorithms. In turn, these algorithms directly convert the data into useful actionable results that can be implemented by the loT devices.
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