This section pulls back the curtain to reveal what DataRobot employees talk about in Slack. No surprises here—data science is still top of mind.
|Single- vs. multi-tenant SaaS||What's the difference between the two deployment options with respect to DataRobot SaaS?|
|ACE score and row order||How is sampling done in EDA2 when calculating ACE scores?|
|Redundant features explained||What makes a feature redundant?|
|Import .tf or .keras?||Have you looked at custom models?|
|N-grams and prediction confidence||What tools help understand n-gram predictions?|
|GPU vs. CPU||What's the difference between GPUs and CPUs?|
|Prediction Explanations on small data||Can you get Prediction Explanations for a small dataset?|
|Neural nets and tabular data||Do you need neural networks for tabular data?|
|PCA and K-Means clustering||What's the impact of PCA on KMeans?|
|Default language change with Japanese||Why did the default language change when modeling Japanese text features?|
|Let's talk target leakage||Why might target leakage show intermittently?|
|Normalizing for monotonicity||Can you help me with monotonicity?|
|An interesting way to use a payoff matrix||Consider justifying cost vs. identifying profit drivers.|
|Target transforms||How does transforming your target help ML models?|
|Dynamic time warping||What should I look out for with dynamic time warping?|
|Multiple reduced feature lists||Can I have multiple Reduced Features lists for one project?|
|NPS in DataRobot||Has anyone worked with net promoter scores (NPS)?|
Updated March 3, 2023
Was this page helpful?
Great! Let us know what you found helpful.
What can we do to improve the content?
Thanks for your feedback!