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A dataset for NLP and climate change media researchers The dataset is made up of a number of data artifacts (JSON, JSONL & CSV text files & SQLite database) Climate news DB, Project's GitHub repository [394] ADGEfficiency Climatext Climatext is a dataset for sentence-based climate change topic detection. HF dataset [395] University of Zurich ...
SAT-4 Airborne Dataset Images were extracted from the National Agriculture Imagery Program (NAIP) dataset. SAT-4 has four broad land cover classes, includes barren land, trees, grassland and a class that consists of all land cover classes other than the above three. 500,000 Images Classification 2015 [172] [173] S. Basu et al. SAT-6 Airborne ...
Before starting a download of a large file, check the storage device to ensure its file system can support files of such a large size, check the amount of free space to ensure that it can hold the downloaded file, and make sure the device(s) you'll use the storage with are able to read your chosen file system.
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC.Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to solve data science challenges.
seed is a type of reference table used in dbt for static or infrequently changed data, like for example country codes or lookup tables), which are CSV based and typically stored in a seeds folder. References
The CIFAR-10 dataset (Canadian Institute For Advanced Research) is a collection of images that are commonly used to train machine learning and computer vision algorithms. It is one of the most widely used datasets for machine learning research. [1] [2] The CIFAR-10 dataset contains 60,000 32x32 color images in 10 different classes. [3]
The name is derived from the term "panel data", an econometrics term for data sets that include observations over multiple time periods for the same individuals, [3] as well as a play on the phrase "Python data analysis". [4]: 5 Wes McKinney started building what would become Pandas at AQR Capital while he was a researcher there from 2007 to ...
A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]