Machine Learning vs Deep Learning – Meaning, Difference & its Future

Machine Learning vs Deep Learning - Meaning, Difference & its future

Artificial Intelligence is gaining a lot of traction in 2022. Many scientists believe that AI is the future. You must have heard about the terms Machine Learning and Deep Learning when the topic of AI pops up. Do these words seem new to you? You’ll be surprised to know that you are using it on daily basis.

This blog will help you understand the meaning, difference, and future of Machine Learning and Deep Learning.

What is Machine Learning?

Machine Learning is a subset of Artificial Intelligence and falls under the umbrella of science relating to Artificial Intelligence. It does not require any explicit programming to perform the given tasks. It is built to learn by itself using data. Structured data is given to it and it can then perform tasks without any human intervention. It only requires to be programmed and fed structured data once. After that, it can easily categorize things like people, food, objects, etc. with self-reliance.

It can absorb unlimited new data and sort the data and act accordingly. It processes the data and gives accurate results. There are different types of Machine Learning like supervised learning, unsupervised learning, and reinforcement learning.

Machine Learning has many definitions but can be better understood with the help of examples. If you want your phone to categorize the images in your gallery then Machine learning is used. You have to tag images once to feed structured data like what is a cat, dog, car, etc. The system then uses that algorithm to feature different objects in the image like facial features, body parts, etc., and give you results with the use of that. Machine Learning has various uses like recommending products, generating recommendations on the internet, filtering spam messages, detecting fraud, etc.

What is Deep Learning?

Deep learning is a subset of machine learning. Although similar to machine learning, it requires more human efforts in programming and setting up the algorithm. It thinks and acts like a machine.

It uses deep neural networks to transfer data between the nodes in highly connected ways. It can be compared to a human brain as it functions similarly. The human brain is also connected with neural networks.

Deep Learning requires heavy programming and feeding and building huge volumes of data. The data has to be more detailed than machine learning. It requires several inputs and after that, it immediately provides the results. There are mainly two types of neural networks: Convolutional Neural Networks and Recurrent Neural Networks.

What are the main differences between Machine Learning and Deep Learning?

When you look closely, you will find some key differences between them both.

Difference Between Machine Learning and Deep Learning
Machine Learning and Deep Learning Meaning
Diffrence Between Machine Learning vs Deep Learning

What is the future of Machine Learning and Deep Learning?

Machine learning and Deep Learning completely rely upon data. Data has become the fuel to the vehicle of the future. Everything can be achieved through the appropriate use of data. Machine Learning andDeep Learning are presently used in many fields like commerce, medicine, smart-tech, etc. In future, these will be used to replace complex human tasks and relieve people. It would be used in luxurious restaurants to hazardous industries. You’ll see machine involvement in almost every task; could be lesser involvement or major involvement. The use of artificial intelligence will also rise beyond games and bring immersive experiences in the field of entertainment.

Related: Top 5 Emerging Machine Learning Trends in 2022

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