: Check if the data is properly divided into training, validation, and test sets to ensure the model's reliability on new data.
: Importing data (e.g., from CSV or JSON) and cleaning text by removing stop words and handling n-grams to improve accuracy. svc.py
: Adhere to the PEP8 style guide —for instance, avoid using lower-case 'l' as a variable name to prevent confusion with the number '1'. Other Possible Contexts Depending on your project, svc.py might instead refer to: : Check if the data is properly divided
: Converting text into numerical data using techniques like TfidfVectorizer or CountVectorizer . svc.py