While working on a machine learning project, getting good results from a single model-training run is one thing, but keeping all of your machine learning experiments organized and having a process that lets you draw valid conclusions from them is quite another
Since I work for one of these companies, some people were surprised that I was so bold in discussing the market. However, I consistently believe that it is worth spreading knowledge about machine learning applications, so that the industry is aware of the solutions available on the market.
Best Tools for Tracking ML Experiments is a collection of helpful resources when it comes to the management of machine learning experiments. Since we made our list a few good weeks ago and the ML industry is changing dynamically, please let us know in case of any comments.
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