DataRobot Reviews

The interface is pretty easy to navigate. It also makes machine learning very accessible cutting down a lot of manual work.

There honestly doesn’t seem much to dislike but sometimes the number of features can feel a bit overwhelming. The learning curve takes some time.

It is definitely helping the with the manual work. Instead of spending weeks in writing codes, we are able to get accurate models in a short span of time.

I really like how quickly I can get useful information out of DataRobot. I can upload my data and start seeing results almost right away, which saves me a ton of time.

The automated modeling is a big help because it tries different approaches for me instead of requiring everything to be done manually. I also appreciate that I can still understand what’s driving the predictions, so it doesn’t feel like a black box.

One downside is that it can feel a bit overwhelming at first. There’s a lot happening in the UI, and it isn’t always clear where to click or what to focus on, especially for new users. A more streamlined layout or a guided experience would make it easier to get started.

It basically helps in deploying and modelling ML models. It is automated technology that helps us in data preprocessing, feature engineering choosing the best model and even hyperparameter tuning. It is time-saving and can handle large data. and always choose best model for our project.

it is costly and not as good as IBM Watson. Sometime it does not gives us the best model and we have to choose ourselves and also customization are limited

Time saving in choosing the best model and data pre-processing.

.Automated feature engineering, multiple algorithms trained, automated comparisons

Limited applications in probabilistic and neural network applications for Customer Lifetime Value prediction

Forecasting and automated outputs

Algorithmia has really put the power back in the hands of our data scientists and R&D developers. One of the key bottlenecks our organization faced was pushing code from dev into production, due to the time spent containerizing our code and the skillset required to do so. Especially in situations when we are constantly iterating and publishing new versions, the ability to containerize without support from dev ops is extremely powerful.

Two of the main areas for improvement would be parity with Azure repos and more business-focused reporting of platform consumption. We have stakeholders in both technical and business areas, and struggle to communicate this across teams. Additionally, SAS is a very popular language in our line of business, which Algorithmia does not currently support.

In addition to the bottleneck from code containerization, Algorithmia has also helped our team with knowledge transfer. Our organization is a large, global company and we have had difficulty in the past with sharing code across teams. Algorithmia has become a centralized platform for our teams to work.

Turn key solution to run any AI/NLP model.

1. Easy deployment and hassle free

2. Version management which will help to test any version.

At Freiburger Energieoptimierung UG (www.frenop.de), DataRobot accelerated the pace of our analytics applied to energy efficiency and savings. Our team is integrated of Physicians who have a great knowledge of physical behaviors but we don’t have the time and the resources to develop a platform where we can analyze data from energy applications. DataRobot offers us automated solutions that are contributing for faster energy data analysis and also new discoveries with Machine Learning. The interface is very easy to use.

DataRobot showed us that we need to have more data in order to proceed with some routines. Now we are investing more in time in finding this data in the real world so we can put it into these machine learning algorithms.

It helping us with everything related to data visualization, data analytics, discovery of patterns, automation of behaviors, tracking of information, definition of different scenarios, controlling issues, performances, etc…

Some structures are very easy to proceed here. Specially for robotics applications.

Nothing to complain at the moment. I am thankful to find good applications for the programed structures that the program offers.

Automation of different interfaces that connect software with virtual reality, robotics and smart actors.

Its very help full to write the algorithm related to machine learning specially developer who want to give certain amount of data to module and model will predict based upon the data give.

Start time is high,when you develop a heavy model some time its hanging

Related to machine learning specially mathematical problems or algorithms

I like how easy it is to collect the data and analyze it!

I dislike inputting all of my data in because it takes a lot of time.

It is great to use! I would definitely recommend it!

It easily analyzed and compared data.