pulkitpahwa · November 11, 2017 05:24 · Nov 11, 2017 · Nov 11, 2017 · Nov 11, 2017
diff --git a/gistfile1.txt b/gistfile1.txt
@@ -65,6 +65,6 @@ For Windows users
 
 5. Execute the command given below
 
-    floyd run --gpu+ --mode jupyter --env tensorflow-1.3 --data analyticsvidhya/datasets/height_n_weight/1:height_n_weight --data analyticsvidhya/datasets/cats_vs_dogs/1:cats_vs_dogs --data analyticsvidhya/datasets/mnist/2:mnist --data analyticsvidhya/datasets/imdb/1:imdb --tensorboard
+    floyd run --cpu --mode jupyter --env tensorflow-1.3 --data analyticsvidhya/datasets/height_n_weight/1:height_n_weight --data analyticsvidhya/datasets/cats_vs_dogs/1:cats_vs_dogs --data analyticsvidhya/datasets/mnist/2:mnist --data analyticsvidhya/datasets/imdb/1:imdb --tensorboard
 
 5. Go to link provided in the terminal (link: https://www.floydhub.com/<user_name>/projects/<project_name>/<job_number>)
diff --git a/gistfile1.txt b/gistfile1.txt
@@ -65,6 +65,6 @@ For Windows users
 
 5. Execute the command given below
 
-    floyd run --gpu --mode jupyter --env tensorflow-1.3 --data analyticsvidhya/datasets/height_n_weight/1:height_n_weight --data analyticsvidhya/datasets/cats_vs_dogs/1:cats_vs_dogs --data analyticsvidhya/datasets/mnist/2:mnist --data analyticsvidhya/datasets/imdb/1:imdb --tensorboard
+    floyd run --gpu+ --mode jupyter --env tensorflow-1.3 --data analyticsvidhya/datasets/height_n_weight/1:height_n_weight --data analyticsvidhya/datasets/cats_vs_dogs/1:cats_vs_dogs --data analyticsvidhya/datasets/mnist/2:mnist --data analyticsvidhya/datasets/imdb/1:imdb --tensorboard
 
 5. Go to link provided in the terminal (link: https://www.floydhub.com/<user_name>/projects/<project_name>/<job_number>)
diff --git a/gistfile1.txt b/gistfile1.txt
@@ -0,0 +1,70 @@
+## Installation Steps
+
+For Mac and Linux users
+
+1. Go to Anaconda page (link: https://www.anaconda.com/download). Download and install the Python 3.6 version. For more info, you can visit this webpage (Mac users: https://docs.anaconda.com/anaconda/install/mac-os, Linux users: https://docs.anaconda.com/anaconda/install/linux)
+
+2. Create a FloydHub account (link: https://www.floydhub.com/signup). Make sure you create a FloydHub account with the same email address with which you have registered for DataHack Summit 2017. Only then we will be able to assign GPU credits.
+
+3. Install FloydHub in your system by going to the terminal by executing 
+
+    pip install -U floyd-cli
+
+4. Now you have to login to FloydHub. Execute the command below in the terminal 
+
+    floyd login 
+
+5. The command above opens up a webpage that displays the authentication token. Copy this token, go to the terminal again and input this token
+
+6. To check if your system is working fine, go through the tutorial mentioned in the webpage (link: https://docs.floydhub.com/getstarted/quick_start/)
+
+
+For Windows users
+
+1. Go to Anaconda page (link: https://www.anaconda.com/download/#windows) and download the appropriate package according to your system (32bit or 64bit). Install the Python 3.6 version. For more info, you can visit this webpage (link: https://docs.anaconda.com/anaconda/install/windows)
+
+2. Create and FloydHub account (link: https://www.floydhub.com/signup). Make sure you create a FloydHub account with the same email address with which you have registered for DataHack Summit. Only then we will be able to assign GPU credits.
+
+3. Install FloydHub in your system by going to the anaconda command prompt by executing 
+
+    pip install -U floyd-cli
+
+4. Now you have to login to FloydHub. Type the command below in the terminal 
+
+    floyd login 
+
+5. The command above opens up a webpage that displays the authentication token. Copy this token, go to the terminal again
+
+6. In the command prompt, hit "backspace" a few times to remove the extra characters from the token login prompt request.
+
+7. Right click on the menu bar, and select "Edit", and then "Paste"
+
+8. Then press "Enter"
+
+9. To check if your system is working fine, go through the tutorial mentioned in the webpage (link: https://docs.floydhub.com/getstarted/quick_start/)
+
+## Steps for running the jupyter notebooks
+
+1. Go to the webpage (link: https://www.floydhub.com/projects/create) and create a new project. Give the project name as tf_workshop
+
+3. Open terminal/anaconda prompt and create a new directory by executing
+
+	mkdir tf_workshop
+
+4. **Change directory** to the created folder by executing
+
+	cd tf_workshop
+
+5. Execute command
+
+    floyd init tf_workshop
+
+6. Execute command 
+
+	floyd clone analyticsvidhya/projects/tf_workshop/1
+
+5. Execute the command given below
+
+    floyd run --gpu --mode jupyter --env tensorflow-1.3 --data analyticsvidhya/datasets/height_n_weight/1:height_n_weight --data analyticsvidhya/datasets/cats_vs_dogs/1:cats_vs_dogs --data analyticsvidhya/datasets/mnist/2:mnist --data analyticsvidhya/datasets/imdb/1:imdb --tensorboard
+
+5. Go to link provided in the terminal (link: https://www.floydhub.com/<user_name>/projects/<project_name>/<job_number>)