AI News, Patterns for Research in Machine Learning
- On Sunday, June 3, 2018
- By Read More
Patterns for Research in Machine Learning
My guess is that these patterns will not only be useful for machine learning, but also any other computational work that involves either a) processing large amounts of data, or b) algorithms that take a significant amount of time to execute.
This is useful because: Create spatial separation between your source code and your data files: This is useful because: Even better would be to always assume that your code and your data are located independently: This is useful because: The data folder will often be too large to store on your machine, and you will have no choice but to separate the two.
For completeness you may also want to: The function get_configurations() can be written in such a way to make the above code segment train 4 different models, one for each valid combination of variables that are being swept over, and store the results in separate directories: This is useful because it makes it easier to try out different algorithm options.
Since the run_experiment() function might potentially be performing complex tasks such as: loading options from disk, sweeping parameters, communicating with a cluster of computers or managing the storing of results, you do not want to have to run the script manually for every run.
- On Tuesday, January 22, 2019
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