IBM Watson Machine Learning vs TensorFlow comparison

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1,809 views|1,240 comparisons
100% willing to recommend
TensorFlow Logo
6,271 views|3,973 comparisons
100% willing to recommend
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Executive Summary

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.
To learn more, read our detailed IBM Watson Machine Learning vs. TensorFlow Report (Updated: March 2024).
768,578 professionals have used our research since 2012.
Featured Review
Quotes From Members
We asked business professionals to review the solutions they use.
Here are some excerpts of what they said:
Pros
"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.""The solution is very valuable to our organization due to the fact that we can work on it as a workflow.""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 most valuable aspect of the solution's the cost and human labor savings."

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"What made TensorFlow so appealing to us is that you could run it on a cluster computer and on a mobile device.""Edge computing has some limited resources but TensorFlow has been improving in its features. It is a great tool for developers.""The most valuable features are the frameworks and the functionality to work with different data, even when we have a certain quantity of data flowing.""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.""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.""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.""It's got quite a big community, which is useful."

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Cons
"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.""In future releases, I would like to see a more flexible environment.""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.""The supporting language is limited.""Scaling is limited in some use cases. They need to make it easier to expand in all aspects."

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"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.""It would be nice to have more pre-trained models that we can utilize within layers. I utilize a Mac, and I am unable to utilize AMD GPUs. That's something that I would definitely be like to be able to access within TensorFlow since most of it is with CUDA ML. This only matters for local machines because, in Azure, you can just access any GPU you want from the cloud. It doesn't really matter, but the clients that I work with don't have cloud accounts, or they don't want to utilize that or spend the money. They all see it as too expensive and want to know what they can do on their local machines.""The solution is hard to integrate with the GPUs.""There are connection issues that interrupt the download needed for the data sets. We need to prepare them ourselves.""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.""TensorFlow Lite only outputs to C.""Personally, I find it to be a bit too much AI-oriented.""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."

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Pricing and Cost Advice
  • "The pricing model is good."
  • "I've only been using the free tier, but it's quite competitive on a service basis."
  • More IBM Watson Machine Learning Pricing and Cost Advice →

  • "TensorFlow is free."
  • "I think for learners to deploy a project, you can actually use TensorFlow for free. It's just amazing to have an open-source platform like TensorFlow to deploy your own project. Here in Russia no one really cares about licenses, as it is totally open source and free. My clients in the United States were also pleased to learn when they enquired, that licensing is free."
  • "We are using the free version."
  • "It is open-source software. You don't have to pay all the big bucks like Azure and Databricks."
  • "I did not require a license for this solution. It a free open-source solution."
  • "I am using the open-source version of TensorFlow and it is free."
  • "I rate TensorFlow's pricing a five out of ten."
  • "It is an open-source solution, so anyone can use it free of charge."
  • More TensorFlow Pricing and Cost Advice →

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    Questions from the Community
    Top Answer: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.
    Top Answer:I've only been using the free tier, but it's quite competitive on a service basis. Heavy data usage and management can drive up the costs, but that's true for most platforms. Ultimately, pricing… more »
    Top Answer:In future releases, I would like to see a more flexible environment. It's a good product for customization and developing products. But when we need the most control over the delivery, Watson isn't… more »
    Top Answer: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.
    Top Answer:It is an open-source solution, so anyone can use it free of charge.
    Top Answer:The versatility of the concept is undeniable, but it can pose a challenge for developers unfamiliar with machine learning. For newcomers to the field, the learning curve can be steep, often requiring… more »
    Ranking
    9th
    Views
    1,809
    Comparisons
    1,240
    Reviews
    3
    Average Words per Review
    526
    Rating
    8.7
    4th
    Views
    6,271
    Comparisons
    3,973
    Reviews
    7
    Average Words per Review
    534
    Rating
    9.0
    Comparisons
    Learn More
    IBM
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    Overview

    IBM Watson Machine Learning helps data scientists and developers accelerate AI and machine-learning deployment. With its open, extensible model operation, Watson Machine Learning helps businesses simplify and harness AI at scale across any cloud.

    TensorFlow is an open source software library for high performance numerical computation. Its flexible architecture allows easy deployment of computation across a variety of platforms (CPUs, GPUs, TPUs), and from desktops to clusters of servers to mobile and edge devices. Originally developed by researchers and engineers from the Google Brain team within Google’s AI organization, it comes with strong support for machine learning and deep learning and the flexible numerical computation core is used across many other scientific domains.

    Sample Customers
    Information Not Available
    Airbnb, NVIDIA, Twitter, Google, Dropbox, Intel, SAP, eBay, Uber, Coca-Cola, Qualcomm
    Top Industries
    VISITORS READING REVIEWS
    Educational Organization20%
    Computer Software Company13%
    University12%
    Financial Services Firm10%
    VISITORS READING REVIEWS
    Manufacturing Company13%
    Computer Software Company12%
    Educational Organization11%
    University9%
    Company Size
    VISITORS READING REVIEWS
    Small Business18%
    Midsize Enterprise24%
    Large Enterprise58%
    REVIEWERS
    Small Business57%
    Midsize Enterprise21%
    Large Enterprise21%
    VISITORS READING REVIEWS
    Small Business20%
    Midsize Enterprise15%
    Large Enterprise65%
    Buyer's Guide
    IBM Watson Machine Learning vs. TensorFlow
    March 2024
    Find out what your peers are saying about IBM Watson Machine Learning vs. TensorFlow and other solutions. Updated: March 2024.
    768,578 professionals have used our research since 2012.

    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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