Likelihood to Recommend Caffe is only appropriate for some new beginners who don't want to write any lines of code, just want to use existing models for image recognition, or have some taste of the so-called Deep Learning.
Read full review Data Robot is a powerful tool for greatly reducing the time required to build powerful and accurate machine learning models. It then allows you to utilize these items. It is probably most appropriate for organisations looking to get into data science and incorporate Machine learning and AI into their decision making. Having dedicated resources that can be upskilled is perfect, as the expertise and software provided allows for a big jump from willing to able. For the to work effectively, organisations should really consider dedicating at least one resource to the ML and AI projects, and understsand that not every project will yield fruit. A lot of this is innovation and experimentation, so relying on data Robots insights in make or break situations is not recommended. You also need to manage expectations well as the data you have may simply not allow for a powerful model. Finally, the organisation must be open to change, this has to exist in tandem with the above. If the organisation's key stakeholders don't want to change, all the insights in the world won't help. So a willingness and ability to change effectively is required to maximize ROI.
Read full review Pros Caffe is good for traditional image-based CNN as this was its original purpose. Read full review DataRobot helps, with algorithms, to analyze and decipher numerous machine-learning techniques in order to provide models to assist in company-wide decision making. Our DataRobot program puts on an "even playing field" the strength of auto-machine learning and allows us to make decisions in an extremely timely manner. The speed is consistent without being offset by errors or false-negatives. It encompasses many desired techniques that help companies in general, to reconfigure in to artificial intelligence driven firms, with little to no inconvenience. Read full review Cons Caffe's model definition - static configuration files are really painful. Maintaining big configuration files with so many parameters and details of many layers can be a really challenging task. Besides imagine and vision (CNN), Caffe also gradually adds some other NN architecture support. It doesn't play well in a recurrent domain, so we have to say variety is a problem. Caffe's deployment for production is not easy. The community support and project development all mean it is almost fading out of the market. The learning curve is quite steep. Although TensorFlow's is not easy to master either, the reward for Caffe is much less than the TensorFlow can offer. Read full review The platform itself is very complicated. It probably can't function well without being complicated, but there is a big training curve to get over before you can effectively use it. Even I'm not sure if I'm effectively using it now. The suggested model DataRobot deploys often not the best model for our purposes. We've had to do a lot of testing to make sure what model is the best. For regressive models, DataRobot does give you a MASE score but, for some reason, often doesn't suggest the best MASE score model. The software will give you errors if output files are not entered correctly but will not exactly tell you how to fix them. Perhaps that is complicated, but being able to download a template with your data for an output file in the correct format would be nice. Read full review Likelihood to Renew DataRobot presents a machine-learning platform designed by data scientists from an array of backgrounds, to construct and develop precise predictive modeling in a fraction of the time previously taken. The tech invloved addresses the critical shortage of data scientists by changing the speed and economics of predictive analytics. DataRobot utilizes parallel processing to evaluate models in R, Python, Spark MLlib, H2O and other open source databases. It searches for possible permutations and algorithms, features, transformation, processes, steps and tuning to yield the best models for the dataset and predictive goal.
Read full review Support Rating As I am writing this report I am participating with Datarobot Engineers in an complex environment and we have their whole support. We are in Mexico and is not common to have this commitment from companies without expensive contract services. Installing is on premise and the client does not want us to take control and they, the client, is also limited because of internal IT regulations ,,, soo we are just doing magic and everybody is committed.
Read full review Alternatives Considered TensorFlow is kind of low-level API most suited for those developers who like to control the details, while
Keras provides some kind of high-level API for those users who want to boost their project or experiment by reusing most of the existing architecture or models and the accumulated best practice. However, Caffe isn't like either of them so the position for the user is kind of embarrassing.
Read full review DataRobot provided the perfect balance of features and price points. The other tools we tried were very expensive and provided extra things that we really didn't need. Some of the other tools also required you to host them on a server at your institution or pay for their cloud service in addition to getting the software. This added to the expense without adding any additional functionality.
Read full review Return on Investment Since we stopped using Caffe before it can reach the production phase, there is no clear ROI that can be defined. Read full review We have been able to cut costs by not buying leads that we will not be able to sell on We have been able to deploy loan eligibility reporting which brought in new business We have been able to improve the performance of our credit providers and our partners which has helped to retain business Read full review ScreenShots