Page 245 - AI Ver 1.0 Class 10
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3. Matplotlib uses a built-in function piecharts() to create pie charts. ….…………….
4. Web Recommendation uses KNN algorithm. ….…………….
5. Personality prediction trait uses Machine Learning algorithm. ….…………….
D. Match the following:
1. Google search a. Pokémon GO
2. Virtual reality b. System maps
3. Fraud and risk detection c. Meaningful information
4. Data features d. Applications of Data Science
5. Data exploration e. Banking sector
SECTION B (Subjective Type Questions)
A. Short answer type questions:
1. In what ways data science is helpful to the airline industry?
Ans. Data Science really proved to be a boon to this industry as it helped to:
• Predict flight delay.
• Decide which class of airplanes to buy.
• Whether to directly land at the destination or take a halt in between.
• Effectively drive customer loyalty programs.
2. Explain the term Outliers Data. Give an example.
Ans. Outliers means the data that differs drastically from the rest of the data. This kind of unusual data needs to
be removed or replaced from the dataset for accurate results. For example: value zero given in marks of a student who
is absent instead of exemption. This will not give an accurate class average.
3. What type of data can be used by Pandas?
Ans. Pandas can be used for the following:
• Tabular data with heterogeneously-typed columns, as in an SQL table or Excel spreadsheet
• Ordered and unordered (not necessarily fixed-frequency) time series data.
• Arbitrary matrix data (homogeneously typed or heterogeneous) with row and column labels.
• Any other form of observational / statistical data sets.
4. Why is KNN called a lazy learner algorithm?
Ans. KNN is also called a lazy learner algorithm because it does not learn from the training set immediately instead it stores
the dataset and at the time of classification, it performs an action on the dataset.
B. Long answer type questions:
1. What are the important points to remember when data is collected?
Ans. While handling data online or offline, the following points to be always remembered:
• The source of data should be authentic and reliable, as the random data source could provide wrong or unusable
data.
• For proper training of AI Model, the authenticity of data is must.
• Privacy of data sources should always be kept in mind, as it is a fundamental right of everyone.
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