This article is from Scikits learn. Scikit-learn Machine Learning in Python is simple and efficient tools for data mining and data analysis. You can check all this information, here.

I put together an in-depth tutorial to explain Transforms (Data Augmentation), the Dataset class, and the DataLoader class in Pytorch. I also show a ton of use cases for different transforms applied on Grayscale and Color images, along with Segmentation datasets where the same transform should be applied to both the input and target images. I show how to do Affine transforms (rotation, translation, shear, zoom), some awesome Image-based transforms (saturation, brightness, contrast, gamma, grayscale). These transforms can be applied with pre-determined settings or randomly sampled from a range of values. I also show some cool utility transforms like type casting, converting to tensors, and going from CHW to HWC.

Here is some great content that you won't find on Google. I hope to add more in the future, and feel free to email me at [email protected] if you want to add some of your links. It is easy to remember this page: the URL is BannedOnGoogle.com. It's not that the articles below are black-listed by Google, but most likely, Google algorithms are not working properly: either they can't find the page or can only find the mobile version (issue with Google's indexation algorithm) or instead, when searching for the article's title, Google returns irrelevant articles, or a copy of the article that is illegaly stolen and hosted elsewhere (issue with Google's web page scoring / ranking / attribution algorithms.) To learn more about these problems (how to design a good search engine or improve Google) click here, and here.

This article is from Scikits learn. Scikit-learn Machine Learning in Python is simple and efficient tools for data mining and data analysis.