Data augmentation
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Augmentation is a process of artificial data generation, which produces a greater volume of data, and thus increasing the likelihood of obtaining higher predictive accuracy of a predictive model.
Usually, a higher volume of data is likely to yield better predictive and more accurate models from training as the algorithm is able to see a greater variety of examples. However, it is not always possible to collect a large amount of data, hence augmentation is required to generate sufficient data to train an accurate predictive model. This is particularly relevant for datasets with images. There are many methods of generating new training examples with images. These include:
- mirroring the image
- adding noise to the image
- distorting the image
Augmentation creates augmented data. Augmented data is based on systematic modification of existing data (with images often through simple linear algebra operations on the whole image) as opposed to synthetic data.
In the current world I see there are tasks that are too complex for programmers to code directly. But with the help of Machine Learning we can train computer systems to explore a large amounts of data and generate a model that will achieve what programmers have set it out to achieve. One of the popular examples is Facebook’s News Feed.
-</ul><p>Augmentation creates <a href="/articles/synthetic-and-augmented-data">augmented data</a>. Augmented data is based on systematic modification of existing data (with images often through simple linear algebra operations on the whole image) as opposed to <a href="/articles/synthetic-and-augmented-data">synthetic data</a>.</p><p> </p><p>In the current world I see there are tasks that are too complex for programmers to code directly. But with the help of <a title="Machine Learning" href="https://intellipaat.com/blog/what-is-machine-learning/"><strong>Machine Learning</strong></a> we can train computer systems to explore a large amounts of data and generate a model that will achieve what programmers have set it out to achieve. One of the popular examples is Facebook’s News Feed.</p>- +</ul><p>Augmentation creates <a title="Synthetic and augmented data" href="/articles/synthetic-and-augmented-data">augmented data</a>. Augmented data is based on systematic modification of existing data (with images often through simple linear algebra operations on the whole image) as opposed to <a title="Synthetic and augmented data" href="/articles/synthetic-and-augmented-data">synthetic data</a>.</p>
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