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fixed link redircting to older version of website and added new link … #768

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fixed link redircting to older version of website and added new link … #768

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2 changes: 1 addition & 1 deletion docs/en/week02/02-3.md
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Expand Up @@ -244,7 +244,7 @@ $$ \frac{\partial \, J(\mathbf{\Theta})}{\partial \, \boldsymbol{W_y}} = \frac{\

The Jupyter notebook can be found [here](https://github.com/Atcold/pytorch-Deep-Learning-Minicourse/blob/master/04-spiral_classification.ipynb). In order to run the notebook, make sure you have `the dl-minicourse` environment installed as specified in [README.md](https://github.com/Atcold/pytorch-Deep-Learning-Minicourse/blob/master/README.md).

An explanation of how to use `torch.device()` can be found in [last week's notes](https://atcold.github.io/pytorch-Deep-Learning-Minicourse/en/week01/01-3/).
An explanation of how to use `torch.device()` can be found in [last week's notes](https://github.com/Atcold/pytorch-Deep-Learning-Minicourse/blob/master/01-tensor_tutorial.ipynb) and an example is shown in [this lecture](https://github.com/Atcold/pytorch-Deep-Learning-Minicourse/blob/master/04-spiral_classification.ipynb).
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This is the correct URL.

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An explanation of how to use `torch.device()` can be found in [last week's notes](https://github.com/Atcold/pytorch-Deep-Learning-Minicourse/blob/master/01-tensor_tutorial.ipynb) and an example is shown in [this lecture](https://github.com/Atcold/pytorch-Deep-Learning-Minicourse/blob/master/04-spiral_classification.ipynb).
An explanation of how to use `torch.device()` can be found in [last week's notes](https://atcold.github.io/pytorch-Deep-Learning/en/week01/01-3/).


Like before, we are going to be working with points in $\mathbb{R}^2$ with three different categorical labels -- in red, yellow and blue -- as can be seen in **Fig. 8**.

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