|
92% SW Score The SW Score ranks the products within a particular category on a variety of parameters, to provide a definite ranking system. Read more
View Details
|
Description | Microsoft Azure is a comprehensive cloud computing platform that is useful for the app developers to build web-based applications on different programming languages such as ASP.NET, Java, PHP, Python, Javascript. Azure enables to quickly create, deploy and manage applications throughout the global network of Microsoft data centres. It can also integrate source code into the hosted apps. It provides development tools for writing and editing code & syntax, debugging and managing development frameworks etc. that help the developers to efficiently build data-driven intelligent apps. Azure also assists in creating Virtual Machine and smart client applications as well as XML web services. Read more | IBM Watson Studio helps to Build, run, and manage AI models. Prepare data and build models anywhere using open source code or visual modeling. Predict and optimize the outcomes. Build, run and manage AI models, and optimize decisions at scale across any cloud. IBM Watson Studio empowers you to operationalize AI anywhere as part of IBM Cloud Pak for Data, the IBM data, and AI platform. Unite teams, simplify AI lifecycle management, and accelerate time to value with an open, flexible multi-cloud architecture. Read more | Amazon SageMaker is a fully integrated service that allows data scientists and developers to easily and quickly train, deploy, and build machine learning models at any range by bringing all bot set capabilities together. It allows users to upload data quickly, tune and train models, compare results and deploy production models all in one place. This software offers a single web-based visual interface to perform all machine learning development steps and enhance data science and team productivity. Moreover, Amazon SageMaker comprises the autopilot features that eliminate the heavy lifting of building a machine learning model and helps users automatically train, build, and tune the ideal machine learning model based on their data. Amazon SageMaker autopilot will automatically search different solutions to discover the best model. Users then can directly deploy the model to production in one click to enhance the model quality. Amazon SageMaker offers other extensive features that assists users in simplifying the data preparation process and helping complete the data preparation workflow. Amazon SageMaker offers a premium and follows a subscription-based pricing strategy. Read more |
Pricing Options |
|
|
|
SW Score & Breakdown |
92% SW Score The SW Score ranks the products within a particular category on a variety of parameters, to provide a definite ranking system. Read more
|
|
|
SaaSworthy Awards | # 2 Most Worthy # 1 Fastest Growing |
Not Available
|
Not Available
|
Organization Types Supported |
|
|
|
Platforms Supported |
|
|
|
Modes of Support |
|
|
|
API Support |
|
|
|
User Rating |
|
|
|
Rating Distribution |
|
|
|
User Sentiments |
Comprehensive Cloud Solutions, Scalability and Flexibility, Ease of Use and Deployment, Robust Security Features Complex Pricing Structure, Occasional Service Disruptions, Steep Learning Curve for Beginners, Limited Customer Support |
User-Friendly Interface, Extensive Machine Learning Capabilities, Easy Model Deployment, Seamless Team Collaboration Limited Third-Party Integrations, Documentation Needs Improvement, Occasional Slow Loading Times, Steep Learning Curve |
Not Available
|
Review Summary |
Overall, user reviews indicate that the product offers high scalability, reliability, and a wide range of features. Users appreciate its flexibility and ease of use, citing the intuitive interface and comprehensive documentation. Praises are also given for the robust security measures and the ability to integrate with other applications. However, some users mention occasional performance issues and limited customer support. Additionally, a few users express concerns about the pricing structure and the complexity of certain features. |
User reviews of IBM Watson Studio highlight its strengths in supporting machine learning model development and deployment, particularly for data scientists. Users appreciate the platform's ease of use, its integration with open-source tools like Jupyter Notebooks and its powerful analytics capabilities. However, some users express concerns about the learning curve, limited support for certain data formats, and integration challenges with non-IBM cloud providers. Additionally, several users point to pricing as a potential barrier for smaller organizations. |
Not Available
|
Read All User Reviews | Read All User Reviews | Read All User Reviews |
AI-Generated from the text of User Reviews
Pricing Options |
|
|
|
Pricing Plans
Monthly Plans
Annual Plans
|
Microsoft Azure Custom |
IBM Watson Studio Custom |
Amazon SageMaker Others |
View Detailed Pricing
|
View Detailed Pricing
|
View Detailed Pricing
|
Microsoft Power Apps
4.4 Based on 177 Ratings
Google Cloud APIs
4.8 Based on 29 Ratings
The m-Power Development Platform
4.9 Based on 25 Ratings
Visual Studio IDE
4.7 Based on 2447 Ratings |
Amazon SageMaker
4.4 Based on 42 Ratings
Google Cloud AutoML
4.3 Based on 22 Ratings
Colabo
4.6 Based on 23 Ratings
BasicAI
4.5 Based on 25 Ratings
Oracle Data Science Cloud Service
4 Based on 6 Ratings |
Databricks
4 Based on 130 Ratings
Azure Machine Learning Studio
4.5 Based on 65 Ratings
Google Cloud AutoML
4.3 Based on 22 Ratings |
|
Screenshots |
+ 5 More
|
Not Available |
+ 1 More
|
Videos |
+ 1 More
|
Company Details | Located in: Redmond, Washington |
Not available |
Not available |
Contact Details |
Not available |
Not available |
Not available |
Social Media Handles |
|
Not available |
Not available |
Looking for the right SaaS
We can help you choose the best SaaS for your specific requirements. Our in-house experts will assist you with their hand-picked recommendations.
Want more customers?
Our experts will research about your product and list it on SaaSworthy for FREE.