| # Example MySQL config file for large systems. | |
| # | |
| # This is for a large system with memory = 512M where the system runs mainly | |
| # MySQL. | |
| # | |
| # MySQL programs look for option files in a set of | |
| # locations which depend on the deployment platform. | |
| # You can copy this option file to one of those | |
| # locations. For information about these locations, see: | |
| # http://dev.mysql.com/doc/mysql/en/option-files.html |
I have a couple of AI/ML projects related to mapping things, often conservation related, with remote sensing data. Some details and packages will vary, but the process below describes how I generally approach these types of problems. Some of these tools I have only touched briefly, but I like them, and this is more an outline of how I would like to approach a new project than a retrospective look at my previous work.
We use AWS, so it makes sense to use datasets and services that are already hosted on AWS. The data discovery and loading part of this process would look somewhat different if we were using Azure and Planetary Computer, and very different if we were using GCP and Earth Engine.
All of my analysis will be done using python on an AWS VM in the same region as my data on S3, Probably using VSCode on Sagemaker or [JupyterLab](https://docs.aws.amazo
| #!/bin/bash | |
| ### steps #### | |
| # verify the system has a cuda-capable gpu | |
| # download and install the nvidia cuda toolkit and cudnn | |
| # setup environmental variables | |
| # verify the installation | |
| ### | |
| ### to verify your gpu is cuda enable check |
