We performed a comparison between IBM Watson Machine Learning 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."Scalability-wise, I rate the solution ten out of ten."
"It has improved self-service and customer satisfaction."
"It is has a lot of good features and we find the image classification very useful."
"I was particularly interested in trying the AutoML feature to see how it handles data and proposes new models. The variety of models it provides is impressive."
"The solution is very valuable to our organization due to the fact that we can work on it as a workflow."
"The most valuable aspect of the solution's the cost and human labor savings."
"TensorFlow improves my organization because our clients get a lot of investment from their investors and we are progressively improving the products. Every six months we release new features."
"Optimization is very good in TensorFlow. There are many opportunities to do hyper-parameter training."
"Google is behind TensorFlow, and they provide excellent documentation. It's very thorough and very helpful."
"It is also totally Open-Source and free. Open-source applications are not good usually. but TensorFlow actually changed my view about it and I thought, "Look, Oh my God. This is an open-source application and it's as good as it could be." I learned that TensorFlow, by sharing their own knowledge and their own platform with other developers, it improved the lives of many people around the globe."
"What made TensorFlow so appealing to us is that you could run it on a cluster computer and on a mobile device."
"TensorFlow is a framework that makes it really easy to use for deep learning."
"It's got quite a big community, which is useful."
"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."
"In future releases, I would like to see a more flexible environment."
"They should add more GPU processing power to improve performance, especially when dealing with large amounts of data."
"Honestly, I haven't seen any comparative report that has run the same data through two different artificial intelligence or machine learning capabilities to get something out of it. I would love to see that."
"The supporting language is limited."
"If I consider how we want to use it in our organization, certain areas of improvement can be addressed. For instance, we want to use it with Generative AI, not like ChatGPT, but in a way intended for industrial use."
"Scaling is limited in some use cases. They need to make it easier to expand in all aspects."
"It would be cool if TensorFlow could make it easier for companies like us to program for running it across different hyperscalers."
"However, if I want to change just one thing in the implementation of TensorFlow functions I have to copy everything that they wrote and I change it manually if indeed it can be amended. This is really hard as it's written in C++ and has a lot of complications."
"The solution is hard to integrate with the GPUs."
"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."
"Personally, I find it to be a bit too much AI-oriented."
"TensorFlow Lite only outputs to C."
"There are a lot of problems, such as integrating our custom code. In my experience model tuning has been a bit difficult to edit and tune the graph model for best performance. We have to go into the model but we do not have a model viewer for quick access."
"For newcomers to the field, the learning curve can be steep, often requiring about a year of dedicated effort."
IBM Watson Machine Learning is ranked 9th in AI Development Platforms with 6 reviews while TensorFlow is ranked 4th in AI Development Platforms with 16 reviews. IBM Watson Machine Learning is rated 8.0, while TensorFlow is rated 9.0. The top reviewer of IBM Watson Machine Learning writes "A highly efficient solution that delivers the desired results to its users". On the other hand, the top reviewer of TensorFlow writes "Effective deep learning, free to use, and highly stable". IBM Watson Machine Learning is most compared with Google Cloud AI Platform and Azure OpenAI, whereas TensorFlow is most compared with Microsoft Azure Machine Learning Studio, Google Vertex AI, OpenVINO, Hugging Face and Azure OpenAI. See our IBM Watson Machine Learning vs. TensorFlow report.
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