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What is Data science and the life cycle of Data science ?

What is Data science? 

Data science is a field of study which is used to extract knowledge and get new insights from large amount of data for decision making and planning. 

Data science involves statistics and applied mathematics, programming, visualization, machine learning and deep learning.


Life cycle of data science:

Life cycle of data science

Depending upon the data science problem and the project, the life cycle and the steps involved may vary. These are the general steps involved in the life cycle of data science.

Step 1: Understanding the problem, requirement and the budget of the project.

Step 2: Data is collected from relevant sources like online social media, surveys etc. This is very important step since this forms the base to achieve the required goals.

Step 3: This is the most essential and time consuming step in the life cycle of data science. Data is cleaned and prepared by merging, treating missing values, deleting unwanted columns and features, removing the outliers etc.

Step 4: We have to identify the problem, whether it is a classification, regression or clustering. Then we have to choose appropriate model and the algorithm.

Step 5: The model is evaluated by various assessment metrics and checked whether the quality is achieved. More than one model can be constructed and evaluated. Finally ideal model can be chosen.

Step 6: This is last step in the life cycle. After assessment the model is deployed. If any other step is done improperly it’ll impact in the final deployment. So each step has to be given importance and has to be done very carefully.




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