192|CHATGPT – AI Model Training and Application

Challenges
, , , ,
1

BYU Student Author: @Jacob_Dutton
Reviewers: @Jimmy_Han, @Dallin_Gardner
Estimated Time to Solve: 30 Minutes

We provide the solution to this challenge using:

  • ChatGPT

Need a program? Click here.

Overview
Welcome to the AI Model Training and Application Challenge. This challenge provides a hands-on introduction to the fundamentals of Artificial Intelligence (AI) and Machine Learning (ML). Through a simulated training exercise using ChatGPT, you’ll explore how AI models are trained and applied, even though ChatGPT itself, as a pre-trained model, does not require this process for tasks like sentiment analysis.

Introduction to AI Model Training
AI involves algorithms that perform tasks requiring human-like intelligence, with Machine Learning being a subset where these algorithms learn from data. Training an AI model typically involves preparing a dataset, which is divided into training and validation sets. The model learns from the training data and is tested with the validation data, adjusting its parameters to improve accuracy and efficiency. This challenge will demonstrate these principles in a simplified context, enhancing your understanding of how AI solutions are developed and deployed.

Objective
To develop a foundational understanding of how AI models are trained and to apply this knowledge by simulating the training process with ChatGPT.

Instructions

  • Simulated Training Exercise:
    • You are provided with a dataset (Training Data.csv) that includes customer reviews labeled with sentiments. Feed this data to ChatGPT so that it can learn to recognize patterns in the data.
  • Model Testing and Quantification:
    • Now upload Test Data.csv to ChatGPT, and instruct it to predict the sentiment for each line using the patterns from the training data. If you would like more accurate results, also instruct ChatGPT to use its best judgement for classification as well as the patterns from the training data.
    • Deliverable: After running the sentiment analysis with ChatGPT, count and report the number of positive and negative sentiments identified in the test data. Provide a brief analysis of the results.
  • Evaluation and Iteration:
    • Evaluate the accuracy of the responses from ChatGPT. Refine your prompts if needed to improve the model’s accuracy and re-test to see if the sentiment count changes.
  • Reflection:
    • Submit a brief reflection including the number of positive vs negative customer reviews from your analysis.

Data Files

Suggestions and Hints

This challenge requires the use of ChatGPT 4.0. As of creating this challenge, ChatGPT3.5 does not allow for the uploading of files.

Solution

One of the nuances with AI is that it will produce a different solution each time. Because of this, there is no exact solution to this challenge. The test data has a total of 10 positive and 10 negative reviews.

Solution Video: Challenge 192|CHATGPT – AI Model Training and Application

2

According to ChatGPT, there were 12 positive results and 8 negative results from the provided sentiments. However, upon further personal analysis, I discovered that two of the positive results the ChatGPT should have been negative. One was sentiment number 8 which stated, “Not worth the price. I feel completely let down by the poor quality.” And the other was sentiment number 14 which stated, “Totally dissatisfied with the purchase. It didn’t meet any of my expectations.” The rest of the results I agree with.

3

Time to complete: 20 mins
Rating: beginning.
After running the sentiment analysis, ChatGpt found that there are 13 reviews with positive sentiments and 7 reviews with negative sentiments in the test data.I found out that there should be 10 positive and 10 negative reviews. It also has different answer each time, it has 9 positive and 5 neutral results the next time.

4

Time to complete: 20 minutes
Rating: beginner
Comments: After running the data through ChatGPT and making some edits, it came back with results of 9 positive sentiments and 11 negative sentiments. However, when I actually went in and counted myself, it was 10 positive and 10 negative. I ran it through again and asked ChatGPT to count a second time and the result that it gave me was 10 positive and 10 negative.