AI Insights: Decoding Product Reviews with Databricks(PySpark) & GPT-2
Hi, everyone! Welcome back to our channel! Today, we've got something exciting for you.
Imagine you're an avid online shopper, constantly exploring new products and reading through numerous reviews.
It's all too familiar, right? The excitement of finding a hidden gem versus the disappointment of a purchase that doesn't quite live up to expectations. Now, what if there was a way to add a powerful tool to your shopping arsenal?
In today's tutorial, we're delving into the world of online shopping and product reviews.We all know the struggle of sifting through endless opinions to make an informed decision. That's where our code comes in! We're going to harness the power of advanced language models, specifically GPT-2, combined with the capabilities of Databricks and PySpark for efficient analysis.
Explanation of the Code:
1. Setting Up Spark and Loading GPT-2 Model:
We kick things off by setting up our Spark environment, the powerhouse for big data processing.
We then load the powerful GPT-2 language model from Hugging Face.
2. Creating a Sample DataFrame with Product Reviews:
Next, we create a DataFrame containing sample product reviews.
This DataFrame will be our playground for sentiment analysis.
3. Sentiment Analysis with GPT-2:
The real magic happens here! We define a special function that uses
GPT-2 to analyze the sentiment of each product review.
The model calculates positive and negative scores, giving us a percentage for each.
4. Categorizing Sentiments:
We categorize the reviews into "Positive," "Negative," or "Neutral" based on their sentiment percentages.
This gives us a quick overview of the emotional tone of each review.
5. We display the results in a user-friendly table,
so we can easily see the sentiment breakdown for each review.
6. Calculating Overall Sentiment Statistics:
To wrap it up, we calculate overall statistics.
How many reviews are positive? Negative? Neutral? We've got the numbers!
GitHub link: https://github.com/ekhosravie/AI-Insi...