anton/mlpractical
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Adding Python/NumPy tutorial credits.

Browse Source
This commit is contained in:
Matt Graham 2016-09-23 13:13:55 +01:00
parent 7fd23d81cf
commit f2b6243a84
1 changed files with 1 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
notebooks/01_Introduction.ipynb
View File

@ -256,7 +256,7 @@
"\n",
"Today's exercises are meant to allow you to get some initial familiarisation with the `mlp` package and how data is provided to the learning functions. Next week onwards, we will follow with the material covered in lectures. \n",
"\n",
"If you are new to Python and/or NumPy and are struggling to complete the exercises, you may find going through [this Stanford University tutorial](http://cs231n.github.io/python-numpy-tutorial/) first helps. There is also a derived Jupyter notebook which you can download [from here](https://github.com/kuleshov/cs228-material/raw/master/tutorials/python/cs228-python-tutorial.ipynb) - if you save this in to your `mlpractical/notebooks` directory you should be able to open the notebook from the dashboard to run the examples.\n",
"If you are new to Python and/or NumPy and are struggling to complete the exercises, you may find going through [this Stanford University tutorial](http://cs231n.github.io/python-numpy-tutorial/) by [Justin Johnson](http://cs.stanford.edu/people/jcjohns/) first helps. There is also a derived Jupyter notebook by [Volodymyr Kuleshov](http://web.stanford.edu/~kuleshov/) and [Isaac Caswell](https://symsys.stanford.edu/viewing/symsysaffiliate/21335) which you can download [from here](https://github.com/kuleshov/cs228-material/raw/master/tutorials/python/cs228-python-tutorial.ipynb) - if you save this in to your `mlpractical/notebooks` directory you should be able to open the notebook from the dashboard to run the examples.\n",
"\n",
"## Data providers\n",
"\n",