Account
Categories
Shobha
Shobha
The best way to predict the future is to invent it

What are the challenges of working with unstructured data, and how can they be overcome?

Unstructured data is difficult to process and analyze because it lacks a predefined format. Challenges include data cleaning, normalization, and extracting meaningful features. Overcome this with text mining, natural language processing (NLP), and data preprocessing techniques.For example, Converting text data into structured format for sentiment analysis
RELATED INTERVIEW QUESTIONS
What is the purpose of the action attribute in HTML forms, and how does it work?
What is the difference between grid-gap and gap?
How do you use Pythons threading and multiprocessing modules together?
What is the impact of the charset attribute in the <meta> tag on page encoding?
How do you measure the generalization error of a machine learning model?
How do you handle imbalanced datasets in classification models?
How does the browser render HTML content from a server response?
What are the different input types in HTML5? Provide examples.
What is the <canvas> tag used for in HTML?
What is hyperparameter tuning, and why is it essential for model optimization? How do you perform hyperparameter tuning effectively?
What is the significance of feature importance in decision tree algorithms?
What is the purpose of box-sizing, and how does it affect layout?
What are the most important performance metrics for classification models?
What are the benefits of using a virtual environment in Python?
What is the significance of the method=post in HTML forms, and how does it differ from method=get?