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IBM Watson Machine Learning pros and cons

Vendor: IBM
4.0 out of 5
 

IBM Watson Machine Learning Pros review quotes

AH
Jan 31, 2021
The most valuable aspect of the solution's the cost and human labor savings.
Anurag Mayank - PeerSpot reviewer
Mar 16, 2023
Scalability-wise, I rate the solution ten out of ten.
RichardXu - PeerSpot reviewer
Nov 5, 2020
The solution is very valuable to our organization due to the fact that we can work on it as a workflow.
Find out what your peers are saying about IBM, TensorFlow, Google and others in AI Development Platforms. Updated: April 2024.
768,578 professionals have used our research since 2012.
MA
Nov 14, 2022
It has improved self-service and customer satisfaction.
MS
Jan 3, 2024
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.
SG
Feb 18, 2021
It is has a lot of good features and we find the image classification very useful.
 

IBM Watson Machine Learning Cons review quotes

AH
Jan 31, 2021
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.
Anurag Mayank - PeerSpot reviewer
Mar 16, 2023
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.
RichardXu - PeerSpot reviewer
Nov 5, 2020
Scaling is limited in some use cases. They need to make it easier to expand in all aspects.
Find out what your peers are saying about IBM, TensorFlow, Google and others in AI Development Platforms. Updated: April 2024.
768,578 professionals have used our research since 2012.
MA
Nov 14, 2022
The supporting language is limited.
MS
Jan 3, 2024
In future releases, I would like to see a more flexible environment.
SG
Feb 18, 2021
They should add more GPU processing power to improve performance, especially when dealing with large amounts of data.