In the AI era, we need to build and deploy the machine learning model. Currently in our project is using the Azure Machine learning studio to preprocessing, cleaning, training and deployment of ML model as client requirement. As my knowledge in my team are using the Azure ML Studio. Currently, we are working to build the semantic text analysis of the documents.
- Easy to create the experiment.
- Easy to adopt the best algorithm.
- Efficient way to deploy the model as a web service.
- Centralized platform for the life cycle of machine learning goal.
- Difficult to integrate the data for creating the model.
- I feels it's costly to use it.
For [a] data scientist require[d] to build a machine learning model, so he/she didn't worry about infrastructure to maintain it.
All kind of feature[s] such as train, build, deploy and monitor the machine learning model available in a single suite.
If someone has [their] own environment for ML studio, so there [it would] not [be] useful for them.
I'm satisfied with the Azure Machine Learning Studio- it fulfilled my goal in a single channel. Even haven't worr[ied] about the maintenance or any fault tolerance. This provide[s] the user interactive UI to grab the features easily. [Their] support teams also very help[ful], they stand with us at any time.