Before jumping into Kaggle, we recommend training a model on an easier, more manageable dataset. This will allow you to become familiar with machine learning libraries and the lay of the land. The key is to start developing good habits, such as splitting your dataset into separate training and...
This “otp.csv” from the Kaggle dataset contains On-Time Performance information as from 23 March, 2016 to 6 November, 2016 : train_id direction ('N' or 'S' direction is demarcated as either Northbound or Southbound) origin ('Warminster', 'Glenside',...'Airport Terminal..') next_stati...
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Lastly, the score returned by the competition metric is the mean taken over the individual average F2 Scores of each image in the test dataset. Kernel Submissions You can make submissions directly from Kaggle Kernels. By adding your teammates as collaborators on a kernel, you can share and edit...
The dataset images are 3-meter spatial resolution, and each is labeled with whether an oil palm plantation appears in the image (0 for no plantation, 1 for any presence of a plantation). The datathon task is to train a model that takes as input a satellite image and outputs a ...
the K most common species across samples of the validation dataset so that K maximises the F1F1-score on this same dataset. K turns out to be XX; ... Submission Format The submission format is a CSV file containing two columns for each sample (row): Id column containing integers ...
The decision to use BatchNorm or not often depends on the specific task and dataset, as well as the computational resources available. LUPIN11 Posted a year ago · 754th in this Competition arrow_drop_up1 more_vert Thank you for sharing your great comparison and explanation! CroDoc Posted...
L'objectif du hackathon est de construire le "meilleur modèle" permettant de classifier une petite image satellite provenant d'un jeu de données nommé "EuroSAT" en 10 classes dites "d'occupation des sols". Cette problématique est un sujet majeur d'utilisation de l'imagerie satellitaire, ca...
In this competition, we will predict whether there is rainfall at a location, based on (processed) infrared satellite image information. You may use any set of techniques that you like. Acknowledgements The dataset is courtesy of UC Irvine's Center for Hydrometeorology and Remote Sensing, includin...
In this competition, we will predict whether there is rainfall at a location, based on (processed) infrared satellite image information. You may use any set of techniques that you like. More details are available on the course website. Acknowledgements The dataset is courtesy of Prof. Alex Ihl...