Likelihood to Recommend Google Cloud AI is a wonderful product for companies that are looking to offset AI and ML processing power to cloud APIs, and specific Machine Learning use cases to APIs as well. For companies that are looking for very specific, customized ML capabilities that require lots of fine-tuning, it may be better to do this sort of processing through open-source libraries locally, to offset the costs that your company might incur through this API usage.
Read full review It has a lot of features that are good for teams working on large-scale projects and continuously developing and reiterating their data project models. Really helpful when dealing with large data. It is a kind of one-stop solution for all data science tasks like visualization, cleaning, analyzing data, and developing models but small teams might find a lot of features unuseful.
Read full review Pros good conversion from the voice to the text speed in the conversion from voice to text time-saving in the conversion activity analysis of the results of the conversion in real time Read full review Integration of IBM Watson APIs such as speech to text, image recognition, personality insights, etc. SPSS modeler and neural network model provide no-code environments for data scientists to build pipelines quickly. Enforced best-practices set up POCs for deployment in production with a minimum of re-work. Estimator validation lets data scientists test and prove different models. Read full review Cons Some of the build in/supported AI modules that can be deployed, for example Tensorflow, do not have up-to-date documentation so what is actually implemented in the latest rev is not what is mentioned in the documentation, resulting in a lot of debugging time. Customization of existing modules and libraries is harder and it does need time and experience to learn. Google Cloud AI can do a better job in providing better support for Python and other coding languages. Read full review The cost is steep and so only companies with resources can afford it It will be nice to have Chinese versions so that Chinese engineers can also use it easily It takes a while to learn how to input different kinds of skin defects for detection Read full review Likelihood to Renew We are extremely satisfied with the impact that this tool has made on our organization since we have practically moved from crawling to walking in the process of generating information for our main task to investigate in the field through interviews. With the audio to text translation tool there is a difference from heaven to earth in the time of feeding our internal data.
Read full review because we find out that DSX results have improved our approach to the whole subject (data, models, procedures)
Read full review Usability So far we have not had any problems with the application, it is extremely easy to use and it is also easy to install. It does not require much training since the instruction is quite clear for its execution and application in the procedures of the company. The team in charge of this application is very pleased to work with this app.
Read full review The UI flawlessly merges this offering by providing a neat, minimal, responsive interface
Read full review Reliability and Availability From time to time there are services unavailable, but we have been always informed before and they got back to work sooner than expected
Read full review Performance Never had slow response even on our very busy network
Read full review Support Rating Every rep has been nice and helpful whenever I call for help. One of the systems froze and wouldn't start back up and with the help of our assigned rep we got everything back up in a timely manner. This helped us not lose customers and money.
Read full review I received answers mostly at once and got answered even further my question: they gave me interesting points of view and suggestion for deepening in the learning path
Read full review In-Person Training The trainers on the job are very smart with solutions and very able in teaching
Read full review Online Training The Platform is very handy and suggests further steps according my previous interests
Read full review Implementation Rating In fact, you only need the basic tech knowledge to do a Google search. You need to know if your organization requires it or not,. our organization required it. And that is why we acquired it and solved a need that we had been suffering from. This is part of the modernization of an organization and part of its growth as a company.
Read full review It surprised us with unpredictable case of use and brand new points of view
Read full review Alternatives Considered These are basic tools although useful, you can't simply ignore them or say they are not good. These tools also have their own values. But, Yes, Google is an advanced one, A king in the field of offering a wide range of tools, quality, speed, easy to use, automation, prebuild, and cost-effective make them a leader and differentiate them from others.
Read full review The main reason I personally changed over from Azure ML Studio is because it lacked any support for significant custom modelling with packages and services such as TensorFlow, scikit-learn, Microsoft Cognitive Toolkit and Spark ML. IBM Watson Studio provides these services and does so in a well integrated and easy to use fashion making it a preferable service over the other services that I have personally used.
Read full review Scalability It helped us in getting from 0 to DSX without getting lost
Read full review Return on Investment Artificial intelligence and automation seems 'free' and draws the organization in, without seeming to spend a lot of funds. A positive impact, but who is actually tracking the cost? We want our employees to use it, but many resist technology or are scared of it, so we need a way to make them feel more comfortable with the AI. The ROI seems positive since we are full in with Google, and the tools come along with the functionality. Read full review Could instantly show data driven insights to drive 20% incremental revenue over existing results Still don't have a real use case for unstructured data like twitter feed Some of the insights around user actions have driven new projects to automate mundane tasks Read full review ScreenShots