From f746a3efe8d0659ba5864dbe926f7e84916c0a43 Mon Sep 17 00:00:00 2001 From: pswietojanski Date: Mon, 28 Sep 2015 18:19:07 +0100 Subject: [PATCH] some more clarifications --- 00_Introduction.ipynb | 14 +++++++++----- 1 file changed, 9 insertions(+), 5 deletions(-) diff --git a/00_Introduction.ipynb b/00_Introduction.ipynb index 6cf69fa..989191f 100644 --- a/00_Introduction.ipynb +++ b/00_Introduction.ipynb @@ -49,7 +49,7 @@ "\n", " * `mkdir -p ~/mlpractical/repos-3rd`\n", "\n", - "And now, let us set an MLP_WDIR environmental variable (MLP Working DIRectory) that denotes an absolute path of working dir pointing to `~/mlpractial`, **add the below line** to your `~/.bashrc` file (if it does not exists, create one!):\n", + "And now, let us set an MLP_WDIR environmental variable (MLP Working DIRectory) that will keep an absolute path of working dir pointing to `~/mlpractial`, **add the below line** to your `~/.bashrc` file (if it does not exists, create one!):\n", "\n", "```\n", "export MLP_WDIR=~/mlpractical\n", @@ -66,11 +66,13 @@ " * `git clone https://github.com/pypa/virtualenv`\n", " * Enter the cloned repository and type ```./virtualenv.py --python /usr/bin/python2.7 --no-site-packages $MLP_WDIR/venv```\n", " * Activate the environment by typing `source ~/mlpractical/venv/bin/activate` (to leave the virtual environment one may type `decativate`)\n", - " * Environments need to be activated every time ones start the new session so add this command to your `~/.bashrc` script, by typing the below command (note, MLP_WDIR export needs to preceed this command and `.` is actually important):\n", + " * Environments need to be activated every time ones start the new session so we will now create a handy alias to it in `~/.bashrc` script, by typing the below command (note, MLP_WDIR export needs to preceed this command):\n", " \n", - " ```. $MLP_WDIR/venv/bin/activate``` \n", + " ```alias activate_mlp=\"source $MLP_WDIR/venv/bin/activate\"```\n", + " \n", + "Then every time you open new session and want to activate the right virtual environment, simply type `activate_mlp` instead `source ~/mlpractical/venv/bin/activate`. Note, you need to re-soure the .bashrc in order alias to be visible in the current session.\n", "\n", - "### Install packages\n", + "### Installing remaining packages\n", "\n", "Then, before you follow next, install/upgrade the following packages:\n", "\n", @@ -348,7 +350,9 @@ "source": [ "### Exercise 3\n", "\n", - "Write your own data provider `MetOfficeDataProvider` that wraps the weather data for south Scotland (could be obtained from: http://www.metoffice.gov.uk/hadobs/hadukp/data/daily/HadSSP_daily_qc.txt). The file was also downloaded and stored in `data` directory for your convenience. The provider should return a tuple `(x,t)` of the estimates over an arbitrary time windows (i.e. last N-1 days) for `x` and the N-th day as the one which model should be able to predict, `t`. For now, skip missing data-points (denoted by -99.9) and simply use the next correct value. Make sure the provider works for arbitrary `batch_size` settings, including the case where single mini-batch is equal to all datapoints in the dataset. Test the dataset in the cell below." + "Write your own data provider `MetOfficeDataProvider` that wraps the weather data for south Scotland (could be obtained from: http://www.metoffice.gov.uk/hadobs/hadukp/data/daily/HadSSP_daily_qc.txt). The file was also downloaded and stored in `data` directory for your convenience. The provider should return a tuple `(x,t)` of the estimates over an arbitrary time windows (i.e. last N-1 days) for `x` and the N-th day as the one which model should be able to predict, `t`. For now, skip missing data-points (denoted by -99.9) and simply use the next correct value. Make sure the provider works for arbitrary `batch_size` settings, including the case where single mini-batch is equal to all datapoints in the dataset. Test the dataset in the cell below.\n", + "\n", + "Tip: To follow with this exercise, copy MNISTDataProvider in dataset.py, rename it to `MetOfficeDataProvider` and reimplement necesarry parts (including the arguments you pass to the constructor)." ] }, {