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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]
Pages in category "Free and open-source video-editing software" The following 6 pages are in this category, out of 6 total. This list may not reflect recent changes .
OpenShot Video Editor is a free and open-source video editor for Windows, macOS, Linux, and ChromeOS. The project started in August 2008 by Jonathan Thomas, with the objective of providing a stable, free, and friendly to use video editor.
The following is a list of video editing software. The criterion for inclusion in this list is the ability to perform non-linear video editing. Most modern transcoding software supports transcoding a portion of a video clip, which would count as cropping and trimming. However, items in this article have one of the following conditions:
Clipchamp is a freemium video editing tool developed by Australian company Clipchamp Pty Ltd., a subsidiary of Microsoft.It is a web-based, non-linear editing software that allows users to import, edit, and export audiovisual material in a web browser window.
Since video editors represent a project with a file format specific to the program, one needs to export the video file in order to publish it.. Once a project is complete, the editor can then export to movies in a variety of formats in a context that may range from broadcast tape formats to compressed video files for web publishing (such as on an online video platform or personal website ...
VSDC Free Video Editor is a non-linear editing (NLE) application developed by Flash-Integro LLC. [1] It can process custom resolutions, including high-resolution footage, 3D, and VR360-degree videos. The software allows applying post production effects, live color correction, and motion tracking.
Major advances in this field can result from advances in learning algorithms (such as deep learning), computer hardware, and, less-intuitively, the availability of high-quality training datasets. [1] High-quality labeled training datasets for supervised and semi-supervised machine learning algorithms are usually difficult and expensive to ...