| Competition | Result | Date |
|---|---|---|
| Housing Prices Competition for Kaggle Learn Users | 16289.80534 (8978/95343) | 22.12.2023 |
| Natural Language Processing with Disaster Tweets (data cleaning + Tfidf and Logistic Regression) | 0.79436 (597/1223)* | 20.04.2024 |
| Natural Language Processing with Disaster Tweets (BERT) | 0.78761 (724/1223)* | 16.04.2024 |
| Natural Language Processing with Disaster Tweets (Tfidf and Logistic Regression) | 0.78700 (728/1223)* | 18.04.2024 |
| Natural Language Processing with Disaster Tweets (own BERT model) | 0.77106 (927/1223)* | 16.04.2024 |
| Natural Language Processing with Disaster Tweets (using only numeric features and Random Forest) | 0.62365 (1071/1223)* | 18.04.2024 |
| Natural Language Processing with Disaster Tweets (word2vec) | 0.57033 (1089/1223)* | 16.04.2024 |
| Titanic - Machine Learning from Disaster (Random Forest Classifier, Logistic Regression Classifier, Decision Tree Classifier, SVM Classifier, KNN Classifier, Naive Bayes Classifier, Voting Classifiers) | 0.77751 (4397/15687)* | 01.05.2024 |
* There is a rolling leaderboard, the place in the leaderboard is from the day of submission.