I started experimenting with AI sentiment analysis and pushed myself to do some coding. It was quite amazing to see how the Python program uses other libraries like TextBlob to analyze text in a phenomenal way. The sentiment polarity function determines if the text is positive, negative, or neutral, which makes the program efficient. Lastly, defining a function was fun, as I passed in parameters into the function which were the text and theoretical number (0.3). Inside the function, there were three conditional statements (if/else conditions) that decided whether the user´s sentiment was positive, negative, or neutral.
Furthermore, I was able to take away a few ideas after requesting some help with final product ideas with my mentor. I am thinking about training a public dataset from Kaggle and using it to enhance the complexity of the program. Another option would be to write code that can analyze customer reviews on a business website like Amazon, Walmart, or others.
I am looking forward to the final presentation night and am starting to prepare my presentation and content. I will also start sending out my final presentation night classroom program flyers as well as invitations to teachers, friends, and others who might be interested in coming.
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