What is data science

Question

Hi

Answer 1

Please try searching for it first there are allready many answers here and on any search engine aswell as on wikipedia.
https://www.sololearn.com/discuss/2432110/?ref=app

Answer 2

From Wikipedia -

"Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, machine learning and big data."

Answer 3

Someone had sad very beautifully that sometimes it's a good practice to use search bar before asking...Oh! I have said this...😁
Try this next time Buddy...

anyway nice question

here comes your answers :

"Data science is an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data. Data science is related to data mining, machine learning and big data."

Answer 4

Use search bar pls

Answer 5

For what ? NINJA TERMUX TECHNOLOGY

Answer 6

What do you want to develop ? NINJA TERMUX TECHNOLOGY

Answer 7

Sorry for chating here dear mods

Answer 8

Good

Answer 9

Can yo give me a web code

Answer 10

To develop

Answer 11

https://www.sololearn.com/Course/data-science/?ref=app

Answer 12

Data science is a multidisciplinary field that deals with enormous information to separate information and surmisings from it. It is a blend of particular programming, computerized reasoning, examination, and AI with math and insights.

The Data science work process gets ready, cycles, investigations, and conveys the information and its experiences to the organizations to upgrade navigation and procedure arranging.
Data Science Lifecycle
Data science work process is a stepwise strategy; this is what the Data Science Lifecycle resembles:
Data Ingestion: Information obtaining, including signal gathering of crude information (both organized and unstructured).
Data Cleaning and Marking: Naming and cleaning of unstructured information to eliminate ambiguities and convert it to a usable structure.
Information Displaying: Applying information demonstrating, characterization/bunching, mining procedures, and fighting to construct a preparation model. Inferring significant experiences by applying factual and reproduction strategies.
Model Arrangement: Making forecasts and creating understandings through prescient investigation, relapse, and progressed examination strategies. Building model information facilitates information perception.
https://www.sevenmentor.com/data-science-course-in-pune.php