10 Questions
Why is it important to declare or formulate a problem statement clearly in data science?
Your whole model and its working depend on your statement.
What is the next step after defining the problem statement in data science?
Data Collection
What is the most favorite thing for data scientists to do after formulating the motive and collecting data?
Data Cleaning
What are the various forms in which data might be found during the data collection process?
Data can be in any form i.e unstructured or structured. It might be in various forms like videos, spreadsheets, coded forms, etc.
What is data cleaning all about?
The removal of missing, redundant, unnecessary, and duplicate data from a collection.
Which programming languages are commonly used for data cleaning?
R and Python.
Why is R preferred over Python in the statistical part?
R has the privilege of more than 12,000 packages.
What is the purpose of data analysis and exploration in data science?
To analyze the structure of data, find hidden patterns, study behaviors, and visualize effects of variables.
What is the purpose of optimization and deployment in the data science process?
To assess the model's performance, optimize it for accurate predictions, and deploy it for practical use.
What is the process of data modeling in data science?
Building a hypothesis model with a suitable algorithm, training the model, and testing it with data.
Explore the multi-step process of data science and the importance of each stage. Learn about the significance of following proper steps to climb the ladder in data science. Dive into the essential elements and value of each step in building a model.
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