Junior Data Scientist at a tech services company with 51-200 employees
Real User
Dec 9, 2019
I liked the data checking feature where it looks at your data and sees how viable it is for use. That's a really cool feature. Automatic assessment of the quality of datasets, to me, seems very valuable.
The key feature is the automated model-building. It has a good UI that will let people who aren't data scientists get in there and upload datasets and actually start building models, with very little training. They don't need to have any understanding of data science.
Artificial Intelligence Engineer at a manufacturing company with 10,001+ employees
Real User
Dec 5, 2019
The most valuable feature is the model-generation. With a nice dataset, Darwin gives you a nice model. That's a really nice feature because, if we're doing that ourselves, it's trial and error; we change the parameters a little and try again. We save time by just giving the dataset to Darwin and letting Darwin generate a model. We find the models it generates are good; better than we can generate.
Darwin has increased efficiency and productivity for our company. With our risk management team, there were models that took them more than three days to process each, only to see the outcome. Now, it takes minutes for Darwin to process the current model. So, we can have it in minutes. We don't have to wait three days for all the models to be tested, then make a decision.
Darwin offers advanced features like automated model-building, data cleaning, and rapid iteration, designed for efficient and intuitive use, enhancing productivity through easy system integration and model optimization.Darwin caters to enterprises needing robust data management and streamlined model development. It provides tools for evaluating dataset quality and resolving data issues such as missing entries or incorrect types. With its REST API, it integrates seamlessly into existing...
I liked the data checking feature where it looks at your data and sees how viable it is for use. That's a really cool feature. Automatic assessment of the quality of datasets, to me, seems very valuable.
The key feature is the automated model-building. It has a good UI that will let people who aren't data scientists get in there and upload datasets and actually start building models, with very little training. They don't need to have any understanding of data science.
The most valuable feature is the model-generation. With a nice dataset, Darwin gives you a nice model. That's a really nice feature because, if we're doing that ourselves, it's trial and error; we change the parameters a little and try again. We save time by just giving the dataset to Darwin and letting Darwin generate a model. We find the models it generates are good; better than we can generate.
In terms of streamlining a lot of the low-level data science work, it does a few things there.
The solution helps with the automatic assessment of the quality of datasets, such as missing data points or incorrect data types.
Darwin has increased efficiency and productivity for our company. With our risk management team, there were models that took them more than three days to process each, only to see the outcome. Now, it takes minutes for Darwin to process the current model. So, we can have it in minutes. We don't have to wait three days for all the models to be tested, then make a decision.
I find it quite simple to use. Once you are trained on the model, you can use it anyway you want.
The thing that I find most valuable is the ability to clean the data.