Artificial Intelligence Class XII Units 1-3

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Questions and Answers

What is the primary question to ask before starting an AI development project?

How many team members are required?

What resources are available for the project?

Is there a pattern in the data? (correct)

What is the budget for the project?

Which question type is associated with clustering in predictive analysis?

Is this unusual?

Which category?

Which group? (correct)

Which option should be taken?

What are the stages of the Design Thinking methodology?

Empathize, Define, Ideate, Prototype, Test (correct)

Empathize, Define, Validate, Prototype, Test

Empathize, Create, Iterate, Test, Learn

Identify, Define, Create, Prototype, Implement

What is a key reason to avoid applying AI techniques?

If there is no pattern in the data Signup and view all the answers

Which type of question does regression in predictive analytics answer?

How much or how many? Signup and view all the answers

Which industry problem is NOT mentioned as a focus for AI application?

Transportation in India Signup and view all the answers

What is the purpose of problem decomposition in computational tasks?

Break down complex problems into manageable units Signup and view all the answers

What is the ultimate goal of employing AI techniques according to the content?

To solve problems with identifiable patterns Signup and view all the answers

What is the total number of variables in the housing dataset?

14 Signup and view all the answers

What percentage of the dataset is typically used for training in a 67-33 split?

67% Signup and view all the answers

Which of the following methods is used to evaluate the model's predictions?

Mean Absolute Error Signup and view all the answers

What is the shape of the dataset after loading it into a Pandas DataFrame?

(506, 14) Signup and view all the answers

What is the purpose of the `train_test_split` function in the model training process?

To split the dataset into training and testing sets Signup and view all the answers

In how many rows does the housing dataset contain observations?

506 Signup and view all the answers

Which machine learning model was utilized to fit the training dataset?

Random Forest Regressor Signup and view all the answers

What programming library is used to load the housing dataset in the example?

Pandas Signup and view all the answers

What does the Airline Passengers dataset primarily represent?

The total number of airline passengers over a period of time Signup and view all the answers

What is indicated by the increasing amplitude of cycles in the Airline Passengers dataset?

It suggests a multiplicative model. Signup and view all the answers

When decomposing the Airline Passengers dataset, which components are extracted?

Observed, trend, seasonal, and residual time series Signup and view all the answers

Which visualization method is used to display the Airline Passengers dataset?

Line plot Signup and view all the answers

What software library is used for seasonal decomposition of the Airline Passengers dataset?

Statsmodels Signup and view all the answers

What is the first step in problem decomposition?

Restate the problem in your own words Signup and view all the answers

What characteristic does the series show according to the line plot review?

Possible linear trend Signup and view all the answers

Which of the following best represents the trend component in time series data?

The long-term overall direction of the data Signup and view all the answers

What does the term 'residuals' refer to in the context of the time series analysis?

Differences between observed values and predicted values Signup and view all the answers

What is a primary goal of those working in AI and Machine Learning as indicated in the content?

To predict outcomes and discover underlying patterns Signup and view all the answers

When creating an app, which aspect is NOT typically considered during the decomposition process?

Who your competitors are Signup and view all the answers

What is the purpose of asking questions for clarification during problem-solving?

To avoid misunderstandings about the problem Signup and view all the answers

In the example of calculating the volume of books, what is the significance of using a loop?

To repeat the volume calculation for each book Signup and view all the answers

During the decomposition of time series data, which of the following describes the seasonality component?

The repeating short-term cycles in the data Signup and view all the answers

Which of the following would be a first step in implementing a solution after understanding the problem?

Think about how to implement one small piece Signup and view all the answers

Why is it important to break complicated pieces down into smaller pieces in problem-solving?

It makes complex problems easier to manage and solve Signup and view all the answers

What major phase follows the selection and scoping of relevant projects in the machine learning lifecycle?

Design/Building the Model Signup and view all the answers

Which programming language is noted as the most popular for building AI models?

Python Signup and view all the answers

What is a critical success factor in the Design/Building phase of AI model development?

Model validation and performance evaluation Signup and view all the answers

Which of the following is NOT an example of productivity-enhancing capabilities in AI development?

User training workshops Signup and view all the answers

What is a significant consideration in the testing phase of AI development projects?

Human biases in selecting test data Signup and view all the answers

Which platform is specifically recognized for helping with feature engineering and hyperparameter optimization?

AutoAI Signup and view all the answers

Which of these does NOT constitute an AI development platform mentioned?

Tableau Signup and view all the answers

What aspect is emphasized as crucial for collaboration during the Design/Building phase?

Access to data, tools, and processes Signup and view all the answers

What does the residual component indicate in the context of time series analysis?

It highlights periods of high variability. Signup and view all the answers

Which of the following best defines the multiplicative model applied to the Airline Passengers dataset?

A model where the seasonal component varies proportionally with the level of the series. Signup and view all the answers

What is suggested by the increasing amplitude of cycles in the Airline Passengers dataset?

There exists a multiplicative seasonality within the dataset. Signup and view all the answers

What type of visualization is primarily used to display the raw observations of the Airline Passengers dataset?

Line plot Signup and view all the answers

In the context of analyzing the Airline Passengers dataset, which component is NOT typically extracted during seasonal decomposition?

Cyclic component Signup and view all the answers

What is the purpose of applying seasonal decomposition to the Airline Passengers dataset?

To identify underlying patterns such as trend and seasonality. Signup and view all the answers

Which library is utilized for performing seasonal decomposition in the analysis of the Airline Passengers dataset?

statsmodels Signup and view all the answers

How many monthly observations are included in the Airline Passengers dataset?

144 Signup and view all the answers

What is more effective at driving action according to the information?

Narratives Signup and view all the answers

Which step is NOT mentioned as a part of telling an effective data story?

Using complex jargon Signup and view all the answers

What percentage of students felt excited about Science in the PRE poll?

40% Signup and view all the answers

After reassessing, which percentage of students felt bored in the POST poll?

12% Signup and view all the answers

What is the first step outlined in the process of telling an effective data story?

Understanding the audience Signup and view all the answers

Which option describes an action taken by the teacher after assessing the students' interests?

Changing his teaching method Signup and view all the answers

What was the percentage of students who felt 'A bit interested' in the PRE poll?

25% Signup and view all the answers

What common factor is shared between both PRE and POST polls?

Interest levels in Science Signup and view all the answers

What is the main purpose of the train-test split method in machine learning?

To evaluate the performance of a model on new data Signup and view all the answers

Which of the following is NOT a consideration when choosing the split percentage for train and test datasets?

Provide equal representation for both sets Signup and view all the answers

What percentage of the dataset is typically assigned to the test set in a common train-test split of 80-20?

20% Signup and view all the answers

Which of the following best describes the training dataset's role in the train-test split evaluation?

It is used to fit the machine learning model Signup and view all the answers

What does a split size of 0.67 for the training dataset imply about the corresponding test dataset size?

0.33 Signup and view all the answers

When is the train-test split evaluation considered appropriate?

When there is a sufficiently large dataset available Signup and view all the answers

Why is there no optimal split percentage for train and test datasets?

It is subjective and varies by project objectives. Signup and view all the answers

Which of the following is a common split percentage used in the train-test approach?

80% for training and 20% for testing Signup and view all the answers

What is the first step in the AI project lifecycle?

Project scoping Signup and view all the answers

Why is defining strategic business objectives important in the scoping phase?

It ensures project stakeholders are in alignment. Signup and view all the answers

What does the phrase 'garbage in, garbage out' imply in the context of AI projects?

High-quality data leads to high-quality models. Signup and view all the answers

During the scoping phase of an AI project, what is a critical component that needs to be evaluated?

Return on investment (ROI) Signup and view all the answers

Which phase comes after project scoping in the AI project lifecycle?

Design or build phase Signup and view all the answers

What major factor must be addressed to ensure success in the scoping phase of AI projects?

Stakeholders' expectations and key resources Signup and view all the answers

In the context of AI model building, what does the term 'success metrics' refer to?

The benchmarks used to evaluate project performance. Signup and view all the answers

What is a potential consequence of poor data quality during the scoping phase?

Ineffective AI algorithms Signup and view all the answers

What is the primary reason narratives are more effective than statistics in driving action?

They reduce ambiguity and connect data to context. Signup and view all the answers

Which of the following steps is NOT involved in telling an effective data story?

Creating random data visualizations Signup and view all the answers

After conducting a poll on students' feelings towards science, what action did the teacher take?

He changed his method of teaching. Signup and view all the answers

What percentage of the dataset is designated for testing in a typical 80-20 split?

20% Signup and view all the answers

In the results of the second poll, which response category showed the highest percentage?

Excited Signup and view all the answers

What does an effective data story primarily aim to communicate?

Important messages in the most effective ways Signup and view all the answers

Which Python library is primarily used for data manipulation before splitting the dataset?

Pandas Signup and view all the answers

Which aspect is essential when developing a narrative for a data story?

Identifying and connecting with the audience Signup and view all the answers

What function is used to split the dataset into training and testing sets?

train_test_split Signup and view all the answers

Which of the following is likely a reason someone might feel bored about science, prior to any instructional changes?

Lack of engaging teaching methods Signup and view all the answers

Which line of code correctly selects the features for prediction in the dataset?

x=data.drop('temp', axis=1) Signup and view all the answers

Which data visualization approach was employed by the teacher to assess student interest in science?

Pie chart Signup and view all the answers

After executing 'x_train, x_test, y_train, y_test=train_test_split(x,y,test_size=0.2)', what is the shape of x_train?

(413, 12) Signup and view all the answers

What is the purpose of using the drop() function when preparing the dataset?

To separate labels from features Signup and view all the answers

Which command is used to load a CSV file into a Pandas DataFrame?

data=pd.read_csv('forestfires.csv') Signup and view all the answers

What is a key role of features in supervised learning?

To predict labels based on their values Signup and view all the answers

What advantage does a larger test set provide when evaluating model quality?

It increases the reliability of the model quality measures. Signup and view all the answers

How does cross-validation differ from a simple train-test split in terms of data usage?

It allows for every data point to be a holdout at some point. Signup and view all the answers

What is one of the main trade-offs when choosing between cross-validation and a train-test split?

Cross-validation may require more computational time. Signup and view all the answers

Why might a smaller dataset be more suited to using cross-validation?

The computational burden is relatively insignificant. Signup and view all the answers

What is a key reason that relying on a single test set can be problematic?

It can lead to randomness affecting the model evaluation. Signup and view all the answers

How many folds are typically used in a standard cross-validation approach described?

5 folds. Signup and view all the answers

What is the impact of increased set size on the noise of model score measurements?

Larger sets reduce the randomness of model quality measures. Signup and view all the answers

What happens at each fold in the cross-validation procedure?

Each fold serves as a holdout set exactly once for evaluation. Signup and view all the answers

Study Notes

Artificial Intelligence Study Material (Class XII)

This document is a teacher instruction manual for a Level 3 AI course (Unit 1-3) for Class 12 students.
It covers three units: Capstone project, Model life cycle, and Story telling through data.
An appendix provides additional resources (Python) for advanced learners.

Unit 1: Capstone Project

Title: Capstone Project
Approach: Hands-on, Teamwork, Web Search, Case Studies
Summary: The final project of the academic program; integration of all prior learning through real-world projects and solutions.
Objectives:
- Apply learning to real world problems
- Clearly communicate solutions using non-technical terms
- Choose and apply appropriate algorithms to solve identified problems
Key Concepts: AI Project Cycle, Model Validation, RMSE, MSE, MAPE
Capstone Project Ideas:
- Stock Price Predictor
- Sentiment Analyzer
- Movie Ticket Price Predictor
- Student Result Predictor
- Human Activity Recognition (Smartphone Data Set)
- Image Classification (Humans and Animals)

Unit 2: Model Life Cycle

Title: Model Life Cycle
Approach: Hands-on, Teamwork, Web Research, Case Studies
Summary: The cyclical process for AI/machine learning projects, typically involving scoping, design, building, deployment, feedback and production.
Objectives:
- Develop capstone projects by applying AI project cycle methodologies
- Break down projects into different phases of the AI project cycle
- Select and apply appropriate AI models to solve problems.
Key Concepts: AI Project Cycle, Model Validation, AI Deployment, IBM Watson

Unit 3: Story Telling Through Data

Why Storytelling is Important: Creates engagement, establishes community, and promotes cross-cultural understanding. Essential part of indigenous cultures.
Data Storytelling Steps:
- Understand the audience
- Choose right data and visualizations
- Emphasize key information
- Develop a narrative
- Engage the audience

Appendix: Additional Resources (Python)

Resources: Python notebooks, links to Open Source GitHub repositories, and eBooks.
Categories: Beginner (no prior Python experience) and Advanced (prior experience).
Availability: Cloud based storage.

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Description

This quiz covers the key concepts and objectives from the AI Level 3 course for Class 12 students, focusing on the Capstone project, model life cycle, and storytelling through data. Students will integrate their learning through real-world projects while applying algorithms and communicating solutions. The quiz also includes resources for advanced learners using Python.