Refactor code structure for improved readability and maintainability

Update model evaluation metrics and classification reports for improved accuracy

Refactor code structure for improved readability and maintainability

Update notebook file size and hash for 04_Training.ipynb

Update notebook file size and hash for 01_EDA_Psort.ipynb

Update dependencies in my_utils.py and clean up imports

Update notebook metadata and remove unnecessary Zone.Identifier file

Refactor fetch_refseq_sequence to improve error handling and input validation

Update README.md: Clarify application description and improve example input/output formatting

Remove outdated environment configuration files and update README with detailed usage instructions for the Protein Location Predictor application. Add error handling for model loading in prediction utility, and include a sample protein sequence in FASTA format. Update the project structure and installation steps to reflect the latest changes.

Plotting of training results

Streamline training of rf and svm models, renameing notebooks, minor changes to my_utils.py and creation of evaluation.csv

Refactor my_utils.py: Simplify type hints, enhance evaluate and training functions, and improve error handling in sequence fetching

Refactor and optimize notebook utilities and model training functions

Update project structure and remove unused notebooks

Add Tkinter-based GUI for Protein Location Prediction

Created CLI prototype, rearregement of files

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