We performed a comparison between IBM Watson Studio and TensorFlow based on real PeerSpot user reviews.
Find out in this report how the two AI Development Platforms solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."The scalability of IBM Watson Studio is great."
"The system's ability to take a look at data, segment it and then use that data very differently."
"It has a lot of data connectors, which is extremely helpful."
"For me, the valuable feature of the solution is the one that I used, which was Jupyter notebooks."
"The most important thing is that it's a multi-faceted solution. It's a kind of specialist, not a generalist. It can produce very specific information for the customer. It's totally different from Google or any search engine that produces generic information. It's specialty is that it's all on video."
"The main benefit is the ease of use. We see a lot of engineers in our site and customers that really like the way the tools are able to work with the people."
"Technical support is great. We have had weekly teleconferences with the technical people at IBM, and they have been fantastic."
"Stability-wise, it is a great tool."
"It empowers us to seamlessly create and deploy machine learning models, offering a versatile solution for implementing sophisticated environments and various types of AI solutions."
"Google is behind TensorFlow, and they provide excellent documentation. It's very thorough and very helpful."
"The most valuable feature of TensorFlow is deep learning. It is the best tool for deep learning in the market."
"Optimization is very good in TensorFlow. There are many opportunities to do hyper-parameter training."
"What made TensorFlow so appealing to us is that you could run it on a cluster computer and on a mobile device."
"It is open-source, and it is being worked on all the time. You don't have to pay all the big bucks like Azure and Databricks. You can just use your local machine with the open-source TensorFlow and create pretty good models."
"TensorFlow is a framework that makes it really easy to use for deep learning."
"TensorFlow provides Insights into both data and machine learning strategies."
"Some of the solutions are really good solutions but they can be a little too costly for many."
"Watson Studio would be improved with a clearer path for the deployment of docker images."
"More features in data virtualization would be helpful. The solution could use an interactive dashboard that could make exploration easier."
"The initial setup was complex."
"I want IBM's technical support team to provide more specific answers to queries."
"We would like to see it more web-based with more functionality."
"Initially, it was quite complex. For us, it was not only a matter of getting it installed, that was just a start. It was also trying to come up with a standard way of implementing it across the entire organization, which had been a challenge."
"The solution's interface is very slow at times."
"It doesn't allow for fast the proto-typing. So usually when we do proto-typing we will start with PyTorch and then once we have a good model that we trust, we convert it into TensorFlow. So definitely, TensorFlow is not very flexible."
"JavaScript is a different thing and all the websites and web apps and all the mobile apps are built-in JavaScript. JavaScript is the core of that. However, TensorFlow is like a machine learning item. What can be improved with TensorFlow is how it can mix in how the JavaScript developers can use TensorFlow."
"TensorFlow Lite only outputs to C."
"It would be nice if the solution was in Hungarian. I would like more Hungarian NAT models."
"In terms of improvement, we always look for ways they can optimize the model, accelerate the speed and the accuracy, and how can we optimize with our different techniques. There are various techniques available in TensorFlow. Maintaining accuracy is an area they should work on."
"There are connection issues that interrupt the download needed for the data sets. We need to prepare them ourselves."
"Personally, I find it to be a bit too much AI-oriented."
"TensorFlow deep learning takes a lot of computation power. The more systems you can use, the easier it is. That's a good ability, if you can make a system run immediately at the same time on the same task, it's much faster rather than you having one system running which is slower. Running systems in parallel is a complex situation, but it can improve. There is a lot of work involved."
IBM Watson Studio is ranked 7th in AI Development Platforms with 13 reviews while TensorFlow is ranked 4th in AI Development Platforms with 16 reviews. IBM Watson Studio is rated 8.2, while TensorFlow is rated 9.0. The top reviewer of IBM Watson Studio writes "A highly robust and well-documented platform that simplifies the complex world of AI". On the other hand, the top reviewer of TensorFlow writes "Effective deep learning, free to use, and highly stable". IBM Watson Studio is most compared with Databricks, Microsoft Azure Machine Learning Studio, Azure OpenAI, Google Vertex AI and Amazon Comprehend, whereas TensorFlow is most compared with Microsoft Azure Machine Learning Studio, Google Vertex AI, OpenVINO, IBM Watson Machine Learning and Hugging Face. See our IBM Watson Studio vs. TensorFlow report.
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