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6 | 6 | %matplotlib inline |
7 | 7 |
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8 | 8 | #%% |
9 | | -# here we are going to see how we can create a neural network and train and test it |
10 | | -# we will see how we can augment our data, create our datasets, etc . lets go |
11 | | -# in Pytorch we can use the torchvision module, for reading existing datasets or create our own |
12 | | -# we also do augmentation using this module. this module also provides several wellknown achitectures |
| 9 | +# Here we are going to see how we can create a neural network and train/test it in Pytorch |
| 10 | +# We will see how we can augment our data, create our datasets, etc and alot more. |
| 11 | +# In Pytorch we can use the torchvision module, for reading existing datasets that Pytorch offers, |
| 12 | +# or create a dataset out of our existing folder of images. |
| 13 | +# It also provides a fakedataset for images, which we can use for benchmarking, or debugging. |
| 14 | +# We also do augmentation using this module. This module also provides several well known achitectures |
13 | 15 | # such as AlexNet, VGGNet, ResNet, MobileNet, DenseNet, etc |
14 | 16 | # enough talking lets see how to use it |
15 | 17 | # here lets import datasets for using the dataset capabilities |
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