Technical Areas:
- Cleaned data using pandas from the scraped csv file that was done last week
- Organized and visualized the data based on categories
Tools:
- Visual Studio Code
- Jupyter Notebook
- Pandas
Soft Skills:
- Understood the code examples from the webinars and resource pdfs on the module by going line by line
- Watched YouTube videos for help
Highlights:
- Successfully cleaned and organized the data to transform them into world embeddings (TF-IDF)
- Visualized the data with graphs and charts
- Learned about the various classification models
Tasks:
- Watched the webinars related to the tasks asked in the module
- Cleaned the data and calculated the distance metric
Problems faced:
- Still not finished with the classification model yet as I’m trying to figure out how to accurate calculate the Accuracy, Precision, Recall, and F1-Score metrics