Thanks for sharing the insights. I can confirm that you need to modify the AMI in the setup.sh file and modify the instanceID in the setup_instance.sh.
The ami-64c5cc1d instance appears to be t2.xlarge which does not have GPU (please correct me if I am wrong).
I guess for those that just want to use CPU for running deep learning algorithms this is an option but it might be more cost effective to run it on a p2 instance with GPU?
I am new to all this so let me know if I am mistaken.
hello, whats the cost savings or charge per hour for the AMI ami-64c5cc1d with 30GB volume size ? I understand the cost for the original setup is $.90 per hour. what will be the new cost ?
I’m new in ML field and other tools mentioned by Jeremy in setup video. I wanted to get your guidance if I should go with Floydhub or follow steps mentioned here to reduce size of volume. I believe both steps are to reduce the cost learner has to pay to complete assignments.
Further, Flyodhub is offering 2 hours in trial version rather than 100 hours than it used to offer previously. So,
Floydhub or
Reduce volume
Also, how much time on an average will it take to complete all assignments?
You can probably expect to spend around seventy hours to complete all the assignments.
I personally went with a reduced volume of 30GB and it’s worked fine for me. When I need more space I attach a larger second volume. I haven’t used Floydhub though, so I can’t comment on it.
Thank you @z0k. I’m new to cloud environment so reducing volume would eventually mean bringing down the cost? Also, just to confirm, it took 70 hours to complete ALL assignments?
I think the 70 hours figure I cited includes working through and experimenting with the lecture notebooks. Based on my first run through the MOOC, I believe it’s a good estimate for the time investment to get the most out of the course.
Hi, everyone!
I am a new member here. Just starting this course today and… already found my first-- how to deploy AWS instance with cost reducement.
So, I have read this thread from the beginning until the end, and have no idea how to deploy the low cost one.
Then, I found out this blog post by Slav Ivanov. I think he also a learner on here.
I try to follow his guidelines and got stuck in the instance deployment-- always failed to bid for spot instances.
Thus, I tried my own way, by using AWS console, which apparently easier for me. (I’m using us-west-2 / Oregon)
I follow the guidelines by Slav Ivanov until 1.2 Virtual Private Cloud (VPC)
After this, I use AWS console to deploy my instance. Open up EC2 Dashboard, click Launch Instance
Click Community AMIs >> Search “ami-64c5cc1d” (it seems this AMI has DL frameworks & Anaconda preinstalled) or “ami-bc508adc” (fast.ai default AMI) >> Select
Choose p2.xlarge >> Next
Network: choose the VPC that we have created by using the guideline on the blog post below.
Subnet: same as #5 step
I enabled “CloudWatch detail monitoring” to keep track my usage. I also enabled “Launch as EBS-optimized instance” to make sure I get a lower price >> Next 8.In Add Storage, input your preferred size (I’m using 30GB like the others suggested on here) and set the volume type as “GP2”. Make sure to uncheck delete on termination >> Next
Select existing security group >> choose default >> Next
Launch
it will appear a new pop up, which asking for the key pair. Select “Choose an existing key pair” >> “aws-key-fast-ai” (we have created it by following the guideline on the blog post below. If we can’t select this option, we may create a “Create a new key pair” option. However, please make sure that we save the key pair by downloading it)
Check the acknowledgment >> Launch instances
Let’s wait for a while and we may start to use it when it’s ready.
Happy learning!