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

more changes to intro

Browse Source
This commit is contained in:
pswietojanski 2015-11-15 16:10:05 +00:00
parent cb6712578d
commit 80661efae1
1 changed files with 2 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

4
06_MLP_Coursework2_Introduction.ipynb
View File

@ -14,7 +14,7 @@
"\n", "\n",
"## Syncing the git repository\n", "## Syncing the git repository\n",
"\n", "\n",
"Look <a href=\"https://github.com/CSTR-Edinburgh/mlpractical/blob/master/gitFAQ.md\">here</a> for more details. But in short, we recommend to create a separate branch for this lab, as follows:\n", "Look <a href=\"https://github.com/CSTR-Edinburgh/mlpractical/blob/master/gitFAQ.md\">here</a> for more details. But in short, we recommend to create a separate branch for the coursework, as follows:\n",
"\n", "\n",
"1. Enter the mlpractical directory `cd ~/mlpractical/repo-mlp`\n", "1. Enter the mlpractical directory `cd ~/mlpractical/repo-mlp`\n",
"2. List the branches and check which are currently active by typing: `git branch`\n", "2. List the branches and check which are currently active by typing: `git branch`\n",
@ -94,7 +94,7 @@
"* `numpy.rollaxis` - allows to shuffle certain axis in a tensor\n", "* `numpy.rollaxis` - allows to shuffle certain axis in a tensor\n",
"* `slice` - allows to specify a range (can be used when indexing numpy arrays)\n", "* `slice` - allows to specify a range (can be used when indexing numpy arrays)\n",
"* `ellipsis` - allows to pick an arbitrary number of dimensions (inferred)\n", "* `ellipsis` - allows to pick an arbitrary number of dimensions (inferred)\n",
"* `max_and_argmax` - `(mlp.layers)` - an auxiliary function we have provided to get both max and argmax of a tensor across an arbitrary axes, possibly in the format preserving tensor's original shape (this is not trivial to do using numpy out-of-the-shelf functionality).\n", "* `max_and_argmax` - `(mlp.layers)` - an auxiliary function we have provided to get both max and argmax of a tensor across an arbitrary axes, possibly in the format preserving tensor's original shape (this is not trivial to do using numpy *out-of-the-shelf* functionality).\n",
"\n", "\n",
"Below cells contain some simple examples showing basics behind tensor manipulation in numpy (go through them if you haven't used numpy in this context before)." "Below cells contain some simple examples showing basics behind tensor manipulation in numpy (go through them if you haven't used numpy in this context before)."
] ]