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Artificial intelligence or AI, as it is widely known, is a broad branch of computer science that is concerned with building smart machines. AI machines are capable of performing tasks that otherwise require human intelligence. Some examples of AI are smart assistants, such as Siri, Alexa, and Google Assistant, self-driving cars, robo-advisors, conversational bots, email spam filters, etc.
Machine learning or ML is a branch of AI and computer science that involves the use of data and algorithms to imitate human learning, without explicit programming, and gradually improve its accuracy. ML is an important component of data science. Using statistical methods, algorithms are trained to make predictions or classifications that can help uncover key insights in data mining projects. These generated insights drive decision-making within applications and businesses that positively impact key growth metrics.
The key differences between AI and ML are:
AI | ML |
AI enables a machine to simulate human behavior | ML is a subset of AI and automatically enables a machine to learn from past data without explicit programming |
AI’s goal is to make a smart, humanlike computer system to solve complex problems | ML’s goal is to enable machines to learn from data and yield accurate output |
AI builds intelligent systems to perform tasks like humans | ML teaches machines with data to perform particular tasks and generate accurate results |
AI’s two main subsets are ML and deep learning | ML’s main subset is deep learning |
AI includes learning, reasoning, and self-correction | ML includes learning and self-correction when introduced to new data |
AI deals with all types of data | ML deals with structured and semi-structured data |
AI’s main applications are automated | personal assistants, customer support using chatbots, online gaming, intelligent humanoid robots, etc. |
ML’s main applications are online recommender | systems, Google search algorithms, Facebook auto friend tagging suggestions, etc. |
We provide free resources, such as blogs, tutorials, and videos, as well as a community where you can learn a lot about AI and ML from subject matter experts. We also provide free courses related to AI and ML that you can start learning to build up your basics.
Deep learning is a subset of ML. Deep learning is concerned with algorithms that are inspired by the structure and function of the brain. These systems are known as artificial neural networks.
The core of deep learning is the capability of training large neural networks due to the present existence of fast enough computers and sufficient data. As larger neural networks are constructed and trained with more and more data, their performance improves significantly. Deep learning is generally different from other ML techniques that reach a plateau in their performance.
There are no prerequisites mandated to start learning AI and ML. As long as you have a good internet connection, you can start taking these free courses.
You can start your journey by learning the fundamentals of AI such as NLP using Python, neural networks and deep learning, logistic regression, linear regression, ML with TensorFlow, time series analysis, etc. Learning the fundamentals will help you get started in your journey to become an AI Engineer in no time.
Today, AI has either conquered or is knocking on the door of almost every industry. In the near future, nearly 80% of emerging technologies will be based on AI.
ML, especially deep learning, is used by AI-powered recommender systems, chatbots, and search engines for online movie recommendations and several other applications.
Therefore, AI and ML can be a rewarding career option. Gaining all the right competencies will help you get a high-paying job in top MNCs around the world.
Many companies are seeking skilled candidates in ML for their AI-powered projects. With the rapid growth of AI and ML in every area, the future for professionals in this domain looks promising.
According to Glassdorr, AI engineers in India earn an average of about ₹949,364 p.a. and about US$119,297 p.a. in the USA.
According to Glassdoor, ML engineers in India earn an average of about ₹898,509 p.a. and US$131,001 p.a. in the USA.
Some of the job responsibilities of an AI engineer are:
Some of the job responsibilities of an ML engineer are: