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I actually disagree, CLI is a big improvement. Vastly more developers are familiar with the command line than RStudio or IPython, including almost all of those
by moconnor 5y ago
I actually disagree, CLI is a big improvement. Vastly more developers are familiar with the command line than RStudio or IPython, including almost all of those who don’t already use some kind of ML.
Two major benefits:
* Approachability. If the first step to trying ML on a problem is “download RStudio and learn how to use a GUI and unfamiliar language” that is a HUGE barrier to entry.
* Confidence - if I’m going to put a model into production and all I have to go on is the output of a self-described novice who “played around in RStudio” a bit, well, that’s not going to happen. There are a million ways they might have messed up.
Tangram nails both of these and I’m excited to see where it goes. Happy to talk to you more (ex startup VP Product, current ML researcher) - DM me on Twitter (yieldthought).
- civilized 5y agoBlindly running a CSV through a black box program is not the way to get confidence in your modeling.
- isabellat 5y agoI couldn’t agree more that a black box does not result in confidence in your modeling! Tangram is not a black box :) we tell you exactly the hyper parameter grid we trained, the settings that led to the best model, and provide explanations per prediction based on SHAP. And if you don’t like our settings, you can pass a config file, specifying everything from the column types in your csv, to the features produced, to the hyper parameters of the models you want trained. https://www.tangram.dev/docs/guides/train_with_custom_configuration https://www.tangram.dev/docs/guides/train_with_custom_config...