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What Is Meant By Data Science

What Is Meant By Data Science


          Data Science is the area that uses the scientific methods, processes, algorithms, and systems to extract the knowledge from the structured and unstructured data across a brand range of application domains. It is related to mining, machine learning, and big data. Data science is the idea to unify statistics, data analytics, informatics, and their related methods. It continues to evolve as one of the most promising and demanding career options.

      There are five stages of data sciences. They are 

1. Capture: It does the work of data entry, signal reception, and data extraction.

2. Maintain: It does the work of data warehousing, data cleansing, data staging, data processing, and data architecture.

3. Process: It does the work of data mining, clustering, data modeling, and data summarization.

4. Analyze: It will do the work of exploratory, predictive analysis, regressing, text mining, and qualitative analysis.

5. Communicate: It does the work of data reporting, data visualization, business intelligence, and also decision making.

About Data Science:

         The term data science was coined in 2008 when the companies realized the need for data professionals. The great data scientists are able to identify the relevant questions and collect data from different data sources and organize the formation. They translate the results into solutions and communicate their findings in a way that positively affects business decisions.

        Machine learning is also called as artificial learning. Machine learning is the science of gaining the computer to act without being explicitly programmed. This statement was given by - Stanford. The above definition explains to us the ideal Machine learning.

Machine learning and artificial intelligence have come to provide meaning in the minds of many people.

However, there is some difference which the readers should recognize. Machine learning is the study of computer algorithms. It improves automatically through experience and the use of data.

         Machine learning basically focuses on the applications that learn from the experience and improve their decision making or the predictive accuracy over time. 

        In data science, the algorithm is a sequential programming that happens in the processing steps. If the algorithm is better, then the decisions will be more accurate and predictions will become faster. 

       Machine learning methods are also called machine learning styles. For supervised machine language, it requires less training data than other machine learning methods.

    With this information, we can say that data science and machine learning are ruling the digital world. So we need to choose wisely.


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