🤖🧠AI vs ML vs DL vs Data Science for absolute beginners

In this video, we will cover the difference between Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL) and Data Science (DS).
Artificial Intelligence (AI):
AI is the science that enable computers to think like humans. AI allows computers to imitate human intelligence and do things that humans do!
AI can make decision (Example: buy/sell stocks), understand text (Example: read articles), and also see (Example: detect faces).
Machine Learning (ML):
Machine Learning is a subfield of Artificial Intelligence that enables machines to improve at a given task with experience without being explicitly programmed.
Deep Learning (DL):
Deep Learning is a subset of machine learning that aims at imitating the human brain using mathematical equations.
The human brain consists of billions of neurons that communicate to each other and enable humans to see, think and make decision.
Features from input data are automatically extracted.
Data Science (DS):
Data science is a science that aims at gaining useful information from data.
Data science can help companies make better decisions.
For example, a bank can analyze customer data and identify which customers have high credit score and tailor products/services to meet their needs.
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Thanks and see you in future videos!
#AI #machinelearning #datascience

[@omarabiad4545]

Thank you so much, I watched a lot of videos and read various articles on the manner, and this is the best, most clear video for me yet.

[@VISHALMAHENDRAnullRA]

that was great. Please make step by step project tutorials for absolute beginners

[@user-dc8vc2mh6z]

Thank you, professor. Great and clear explanation.

[@annarodionova8564]

thanks, very clear explanation

[@mahmoudreda9110]

Awesome 👌 👏 thanks

[@pfever]

Thank you, What about Data Mining?

[@franciscodiaz183]

Very nice video, thanks professor.

[@professor-ryanahmed]

Glad you liked it! thanks Francisco :)

[@neeruchauhan1080]

Great video

[@krishnan5567]

Required your email id as we need to present an authoring opportunity.

[@professor-ryanahmed]

Hi Krishna, here you go: [e-mail]