What is Google Cloud Vertex AI?
Cloud Machine Learning Engine is a managed service that lets developers and data scientists build and run superior machine learning models in production. Cloud ML Engine offers training and prediction services, which can be used together or individually. It has been used by enterprises to solve problems ranging from identifying clouds in satellite images, ensuring food safety, and responding four times faster to customer emails. The training and prediction services within ML Engine are now referred to as AI Platform Training and AI Platform Prediction.
Company Details
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Real user data aggregated to summarize the product performance and customer experience.
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Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
89 Likeliness to Recommend
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Since last award
100 Plan to Renew
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Since last award
76 Satisfaction of Cost Relative to Value
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Since last award
Emotional Footprint Overview
Product scores listed below represent current data. This may be different from data contained in reports and awards, which express data as of their publication date.
+92 Net Emotional Footprint
The emotional sentiment held by end users of the software based on their experience with the vendor. Responses are captured on an eight-point scale.
How much do users love Google Cloud Vertex AI?
Pros
- Inspires Innovation
- Performance Enhancing
- Effective Service
- Respectful
How to read the Emotional Footprint
The Net Emotional Footprint measures high-level user sentiment towards particular product offerings. It aggregates emotional response ratings for various dimensions of the vendor-client relationship and product effectiveness, creating a powerful indicator of overall user feeling toward the vendor and product.
While purchasing decisions shouldn't be based on emotion, it's valuable to know what kind of emotional response the vendor you're considering elicits from their users.
Footprint
Negative
Neutral
Positive
Feature Ratings
Model Training
Data Exploration and Visualization
Data Labeling
Feature Engineering
Explainability
Data Ingestion
Openness and Flexibility
Pre-Packaged AI/ML Services
Model Monitoring and Management
Algorithm Diversity
Data Pre-Processing
Vendor Capability Ratings
Quality of Features
Ease of Data Integration
Ease of Implementation
Ease of Customization
Ease of IT Administration
Business Value Created
Breadth of Features
Vendor Support
Availability and Quality of Training
Product Strategy and Rate of Improvement
Usability and Intuitiveness
Google Cloud Vertex AI Reviews
Ekta S.
- Role: Information Technology
- Industry: Finance
- Involvement: End User of Application
Submitted Mar 2024
Google Vertex AI: Simplifying AI Development.
Likeliness to Recommend
What differentiates Google Cloud Vertex AI from other similar products?
Google Cloud Vertex AI distinguishes itself by providing a comprehensive platform for machine learning development. Its unified approach streamlines the entire process from data preparation to model deployment. With powerful AutoML capabilities, it enables users to create custom models with ease. Integration with Google Cloud services enhances workflow efficiency. Moreover, Vertex AI offers scalability, performance, pre-built models, and advanced monitoring tools, making it a robust solution for businesses and developers in the AI space.
What is your favorite aspect of this product?
One of the standout features of Google Vertex AI is its seamless integration with Google Cloud services, which greatly simplifies the machine learning development process. Leveraging the extensive capabilities of Google Cloud allows for efficient data management, processing, and analysis, enabling developers to focus more on building and refining their models rather than managing infrastructure. This integration enhances productivity and accelerates the deployment of AI solutions, making Vertex AI a preferred choice for ML projects.
What do you dislike most about this product?
One potential drawback of Google Vertex AI could be its learning curve for users who are new to the platform or have limited experience with machine learning. While it offers powerful features and capabilities, navigating the interface and understanding the various components may require some time and effort. Additionally, the pricing structure of Google Cloud services, including Vertex AI, could be complex for some users to grasp initially, potentially leading to unexpected costs.
What recommendations would you give to someone considering this product?
Familiarize yourself with Google Cloud platform basics for seamless integration. Start with tutorials and documentation to understand Vertex AI's capabilities and workflow. Experiment with pre-built models and AutoML features to accelerate model development. Utilize Google Cloud's extensive resources for data management and analysis. Stay updated on new features and best practices through Google's support channels and community forums. Consider cost management strategies to optimize spending on resources and services.
Pros
- Helps Innovate
- Continually Improving Product
- Performance Enhancing
- Enables Productivity
Neelam V.
- Role: Consultant
- Industry: Engineering
- Involvement: Business Leader or Manager
Submitted Mar 2024
Robust functionality, yet lacks userfriendly .
Likeliness to Recommend
What differentiates Google Cloud Vertex AI from other similar products?
Google Cloud Vertex AI sets itself apart with its integrated AI platform that simplifies the ML workflow, offers both AutoML and custom model support, provides pre-trained APIs for common tasks, includes advanced MLOps features for seamless model management, benefits from seamless integration with Google Cloud services, and leverages Google's infrastructure for scalability and performance.
What is your favorite aspect of this product?
My favorite aspect of Google Cloud Vertex AI is its integrated AI platform, which streamlines the entire machine learning workflow. This integration not only simplifies the process of developing, deploying, and managing ML models but also significantly reduces the complexity and time required to bring AI solutions to market.
What recommendations would you give to someone considering this product?
Start with the Documentation: Spend some time with Google Cloud's comprehensive documentation and tutorials. They provide a solid foundation for understanding how to use Vertex AI effectively, covering everything from basic concepts to advanced techniques. Experiment with AutoML: If you're new to machine learning or looking for a quick way to deploy models, begin with Vertex AI's AutoML capabilities. It's a great way to familiarize yourself with the platform's functionalities without deep technical knowledge in ML model development.
Pros
- Helps Innovate
- Continually Improving Product
- Performance Enhancing
- Enables Productivity
Shivam K.
- Role: Information Technology
- Industry: Technology
- Involvement: IT Development, Integration, and Administration
Submitted Mar 2024
Easy to use, but a bit pricey.
Likeliness to Recommend
What differentiates Google Cloud Vertex AI from other similar products?
Google Cloud Vertex AI provides a unified AI platform for building, deploying, and managing machine learning models, offering autoML capabilities, and supporting TensorFlow, PyTorch, and XGBoost.
What is your favorite aspect of this product?
Google Cloud Vertex AI is its ability to simplify and streamline the machine learning workflow, making it easier for developers to build and deploy models.
What do you dislike most about this product?
Pricing of Google Cloud Vertex AI to be a bit complex or expensive, depending on their usage needs.
What recommendations would you give to someone considering this product?
1. Start with the free tier or use the pricing calculator to estimate costs.
Pros
- Helps Innovate
- Reliable
- Performance Enhancing
- Enables Productivity
