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Please refer to the doc file for the project description. The pptx file shows the template of presentation and excel file includes the text data to review.

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Week Introduction
This week focuses on evaluating AI and ML models using various metrics. Students will learn about different evaluation metrics and their applications, performing a comparative analysis on a dataset selected by the student.
Week Objectives 
At the end of this week students will be able to:
· Describe different evaluation metrics for ML models. (CO2)
· Apply various evaluation metrics to a classification problem. (CO3)
· Compare the effectiveness of different evaluation metrics. (CO4)
 
Online Lecture 
 
The instructor will post the video recorded from this week's synchronous session here.
 
Below is an outline of the items for which you will be responsible throughout the week.
 
Reading with a due date
DUE: Early in the week
12 Important Model Evaluation Metrics for Machine Learning Everyone Should Know (Updated 2023)
https:
www.analyticsvidhya.com
log/2019/08/11-important-model-evaluation-e
or-metrics/Links to an external site.
Evaluating the Quality of Machine Learning Explanations: A Survey on Methods and Metrics
https:
www.mdpi.com/ XXXXXXXXXX/10/5/593/pdfLinks to an external site.
Model Evaluation Techniques in Machine Learning (python example at end)
https:
medium.com/@fatmanurkutlu1/model-evaluation-techniques-in-machine-learning-8cd88deb8655Links to an external site.
 
Lecture with a due date
DUE: Early in the week
How to evaluate ML models | Evaluation metrics for machine learning
https:
www.youtube.com/watch?v=LbX4X71-TFILinks to an external site.
Metrics and evaluation of machine learning models
https:
www.youtube.com/watch?v=u1-m_hsF7DELinks to an external site.
Evaluating Machine Learning Models
https:
www.youtube.com/watch?v=FeKSQy5t_TILinks to an external site.
Evaluating Classification and Regression Machine Learning Models
https:
www.youtube.com/watch?v=pyl6fO4C7h4Links to an external site.
 
Additional Resources (reading + videos)
No Due date
No additional resources.
 
Submit your completed written assignment by Day 7 of this week.  For detailed instructions on completing this assignment, see the associated course page.
Week 6 Assignment – DUE: Day 7
Week 6 Assignment
Instructions:
Conduct a comparative analysis of different evaluation metrics for a classification problem. Use a dataset and demonstrate the application of at least three metrics. Submit your code AND a separate 1-page report on your approach and results. Use Jupyter notebooks for coding.
Your essay should be at least 2-3 pages in length, not including cover sheet and reference page, and fully explore all of the following items described above. Include at least 2 outside citations and use proper APA formatting.
This assignment is worth 100 points towards the maximum 1460 points you can earn in class.
Answered 3 days After Oct 10, 2024

Solution

Bhaumik answered on Oct 14 2024
3 Votes
Report File
I. Business Context, Problem Overview, and Solution Approach
Customer input is very important in today's cutthroat business environment as it helps shape products and services. Businesses deal with an enormous amount of feedback in the form of reviews, ratings, and comments, especially in customer-focused industries like restaurants. In addition to taking a lot of time, manually analyzing this data to extract insights, pinpoint important areas for development, and quickly address consumer problems is prone to human e
or. Enhancing response time, customer happiness, and retention requires automating sentiment analysis and review categorization.
The main goal of this project is to utilize Prompt Engineering to analyze restaurant reviews by classifying user comments, analyzing sentiment, making recommendations for actions, and utilizing generative artificial intelligence (AI) to automatically generate answers.
II. Prompt and the Structure of the Prompt
Generative AI, such as ChatGPT, is used in the answer to:
· Sort reviews according to pertinent categories, such as price, atmosphere, meal quality, or service.
· Examine the review's attitude (neutral, negative, or favorable).
· To enhance the client experience, make recommendations for activities based on the category and emotion.
· Provide individualized replies for the clients.
Creating structured prompts for AI to provide these outputs and utilizing various prompting strategies (such as zero-shot and few-shot learning) to assess and improve the AI's performance comprise the solution approach.
III. Exploring Different Prompting Techniques
Structure of the Prompt:...
SOLUTION.PDF

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