Data Science plays a vital role in identifying and mitigating fraud in which industry?

Finance

Fill in the blank: The process of predicting food quantity in restaurants is primarily based on ___ data.

Historical

True or False: The K in K-Nearest Neighbours represents the distance metric used in the algorithm.

False. The K represents the number of nearest neighbours considered.

What is the primary purpose of using regression models in the context of restaurant food prediction?

To predict the quantity of food needed for the next day based on historical consumption data.

Riddle: I help you understand data through visual means, but I am not a person. What am I?

Data visualization tools, like Matplotlib.

Fill in the blank: The algorithm KNN uses the characteristics of the nearest points to ___ unknown points.

Classify

Which Python library is primarily used for data manipulation and analysis in Data Science?

Pandas

True or False: Outliers in a dataset are considered errors and should be removed from analysis.

False. Outliers are included for visualization purposes as they provide insight into data distribution.

What is the relationship between data quality and the reliability of AI models?

High-quality data is crucial for training AI models, as unreliable data can lead to inaccurate predictions and poor model performance.

MCQ: Which of the following is NOT a key statistical concept in Data Science? A) Mean B) Median C) Mode D) Syntax

D) Syntax

Fill in the blank: The primary objective of data collection in any AI project is to gather ___ for training and testing.

Data

Riddle: I can tell you how much variation exists in your data, but I am not a person. What am I?

Standard Deviation

What is the importance of the System Map tool in data analysis for AI projects?

The System Map illustrates the relationships between various factors affecting the project's objective, helping to understand and address the problem effectively.

What is the purpose of data cleaning in the data analysis process?

Data cleaning ensures that the dataset is free from errors, missing values, and inconsistencies, which is essential for accurate analysis and model training.

True or False: Data Science can only be applied to numerical datasets.

False. Data Science can also work with categorical and alphanumeric datasets.