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fix cheat sheet link

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franzi
2021-11-19 09:49:30 +01:00
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notebooks/7_hard_drive_failures.ipynb
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@@ -117,7 +117,7 @@
"metadata": {}, "metadata": {},
"source": [ "source": [
"-------------------------------------------------------------------------------------\n", "-------------------------------------------------------------------------------------\n",
"You're already given this rudimentary prediction pipeline, now your job is to improve it. Below are some things you might want to try, but feel free to get creative! Have a look at the [cheat sheet](https://github.com/cod3licious/ml_exercises/blob/main/other/cheatsheet.pdf) for more ideas and a concise overview of the relevant steps when developing a machine learning solution in any data science project. \n", "You're already given this rudimentary prediction pipeline, now your job is to improve it. Below are some things you might want to try, but feel free to get creative! Have a look at the [cheat sheet](https://franziskahorn.de/mlws_resources/cheatsheet.pdf) for more ideas and a concise overview of the relevant steps when developing a machine learning solution in any data science project. \n",
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"The previous notebook, \"analyze toydata\", deals with a very similar problem and can serve as a guideline for this exercise. For an example of how to use the t-SNE algorithm, have a look at the first notebook, \"visualize text\" (but please note that since you don't have sparse data here, there is no need to transform the data with a kernel PCA before using t-SNE).\n", "The previous notebook, \"analyze toydata\", deals with a very similar problem and can serve as a guideline for this exercise. For an example of how to use the t-SNE algorithm, have a look at the first notebook, \"visualize text\" (but please note that since you don't have sparse data here, there is no need to transform the data with a kernel PCA before using t-SNE).\n",
"\n", "\n",