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Using the essay of Judy Brady " I Want A Wife" 1971 , write your own literary critique with a minimum of three (3) and a maximum of five (5) paragraphs. Use any of the six approaches to literary criticism ( Structuralist, Moralist, Marxist, Feminist, Historical, Reader-response). Be guided with the rubric given below.
Literary Analysis Rubric:
▪️Includes a thoughtful introduction tahat names the literary work and clearly states your overall response to it.
▪️Tells enough about the plot, characters, and setting so that readers can clearly understand your response.
▪️Shows your thorough understanding of the theme.
▪️Supports your statements with extensive textual evidence.
▪️Summarize your response in a well-constructed conclusion.
▪️ Consistent point of view, focus, and organization, including effective use of transitions.
Linear Regression Assignment
1. Load the dataset using pandas
2. Extract data fromYearsExperience column is a variable named X
3. Extract data from salary column is a variable named Y
4. Divide the dataset into two parts for training and testing in 66% and 33% proportion
5. Create and train LinearRegression Model on training set
6. Make predictions based on the testing set using the trained model
7. Check the performance by calculating the r2 score of the mode
Directions: Read Judy Brady’s essay, “I want a Wife” (1971). Then, answer the questions that follow.
1. Structuralist: What is the essay about? What themes or patterns are constantly repeated in this literature?
2. Moralist: How does the text play out ethical principles?
3. Marxist: What role does class play in the work? What is the author analysis of class relations?
4. Feminist: How is the work gendered? Where does the text define the roles of femininity?
5. Historical: What assumptions does Brady make about her audience? About wives? Her essay was written in 1971—does still makes sense today? Why or why not?
6. Reader-response: Do you agree or disagree with the writer’s perspective? Why or why not?
Naïve-Bayes Assignment
1. Load the dataset using pandas
2. Extract data fromOutcome column is a variable named Y
3. Extract data from every column except Outcome column in a variable named X
4. Divide the dataset into two parts for training and testing in 70% and 30% proportion
5. Create and train Naïve Bayes Model on training set
6. Make predictions based on the testing set using the trained model
7. Check the performance by calculating the confusion matrix and accuracy score of the model
Decision Tree Assignment
1. Load the dataset using pandas
2. Extract data fromOutcome column is a variable named Y
3. Extract data from every column except Outcome column in a variable named X
4. Divide the dataset into two parts for training and testing in 70% and 30% proportion
5. Create and train Decision Tree Model on training set
6. Make predictions based on the testing set using the trained model
7. Check the performance by calculating the confusion matrix and accuracy score of the model
1. Load the dataset using pandas
2. Extract data fromYearsExperience column is a variable named X
3. Extract data from salary column is a variable named Y
4. Divide the dataset into two parts for training and testing in 66% and 33% proportion
5. Create and train LinearRegression Model on training set
6. Make predictions based on the testing set using the trained model
7. Check the performance by calculating the r2 score of the model
Why air is better than water for respiratory in man?
Explain the concept and importance of a thermodynamic cycle.
An Otto cycle operates on 1lb/s of air from 15 psia and 130 F at the beginning of
compression. The temperature at the end of combustion is 5,000 R; compression ratio is 5.5. for
hot-air standard k=1.32. find (a) T4, OR; (b)P4, psia; (c) Qr, BTU/s; (d) thermal efficiency, and (e)
work net in horsepower.
A Carnot engine operating between 527C and 27 C produces 600KW of work. Determine,
(a) Qa, KW; (b) Qr, KW; (c) ΔS during heat rejection, KW/K and (d) thermal efficiency of the cycle.
#340153 on Dec 2023