- Kernel: A modest example on the Levenshtein distance
- Kernel: TestingStreamlit
- Kernel: Favorita Forecasting model (1 bronze medal)
- Kernel: Titanic dataset (my first submission)
- Kernel: DecisionTree_with_Iris_Dataset
- Kernel: LogisticRegression_on_Complete_Titanic_Dataset
- Kernel: SentimentAnalysis_IMDB_50K_Movie_Review (1 bronze medal)
- Kernel: KC_Houses_With_LinearRegression
- Kernel: Use ngrok with streamlit (just a simple example)
🎯
Focused
Lifelong learning ( ͡~ ͜ʖ ͡°)
- Italy
-
23:00
(UTC +01:00) - https://it.linkedin.com/in/francescopl
- https://www.kaggle.com/francescopaolol
Pinned Loading
-
-
FavoritaTimeSeriesForecasting
FavoritaTimeSeriesForecasting PublicSee: https://www.kaggle.com/competitions/store-sales-time-series-forecasting
Jupyter Notebook 2
-
SentimentAnalysis
SentimentAnalysis PublicAbout sentiment analysis on IMDB Dataset of 50K Movie Reviews
Jupyter Notebook 3
-
-
LearningNLP_with_Transformers
LearningNLP_with_Transformers PublicJust what I'm learning about NLP with Transformers
Python 1
Something went wrong, please refresh the page to try again.
If the problem persists, check the GitHub status page or contact support.
If the problem persists, check the GitHub status page or contact support.