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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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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
100 Plan to Renew
77 Satisfaction of Cost Relative to Value
1
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
- Performance Enhancing
- Inspires Innovation
- Respectful
- Reliable
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
Explainability
Feature Engineering
Data Labeling
Model Monitoring and Management
Data Ingestion
Openness and Flexibility
Pre-Packaged AI/ML Services
Model Tuning
Algorithm Diversity
Vendor Capability Ratings
Ease of Customization
Quality of Features
Ease of Data Integration
Ease of Implementation
Ease of IT Administration
Business Value Created
Breadth of Features
Availability and Quality of Training
Vendor Support
Product Strategy and Rate of Improvement
Usability and Intuitiveness
Google Cloud Vertex AI Reviews
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Siddharth C.
- Role: Information Technology
- Industry: Telecommunications
- Involvement: End User of Application
Submitted May 2024
Enhancing ML with vertex AI
Likeliness to Recommend
What differentiates Google Cloud Vertex AI from other similar products?
Since vertex Ai is part of Google cloud environment the data we use for model development is easy to integrate and provides more layers of security. Integrating with data pipelines and other dependencies is made easier. Auto ML features are also more profound compared to other platforms.
What is your favorite aspect of this product?
Use of tensor flow for processing and other google owned libraries and resources makes it lot faster and convinient for model development and deployment. Deployment to cloud is also a matter of minutes.
What do you dislike most about this product?
Notebooks in vertex Ai could be mare more in sync with other googles visualization tools for the Analytical team with less coding base can visualize data that is in transit instead to wait till finish of the model.
What recommendations would you give to someone considering this product?
People who operate on cloud based environments should consider this as a choice without thinking much. It is cost efficient, user friendly, anyone who used Jupiter or Google Collab can easily be familiar with the environment.
Pros
- Efficient Service
- Reliable
- Performance Enhancing
- Enables Productivity
Cons
- Vendor's Interest First
- Under Delivered
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Atharva V.
- Role: Information Technology
- Industry: Technology
- Involvement: IT Development, Integration, and Administration
Submitted Apr 2024
Exciting Potential of Vertex AI
Likeliness to Recommend
What differentiates Google Cloud Vertex AI from other similar products?
Google Cloud Vertex AI is unique because it easily fits into Google Cloud's setup, making it simple to work with services such as BigQuery and TensorFlow. Plus, its automated machine learning tools make it easier for users at any skill level to build models, simplifying everything from preparing data to putting models into implementation.
What is your favorite aspect of this product?
What I really like about this product is how easily it works alongside other Google Cloud services, making everything flow more smoothly. Also, the automated machine learning tools are a big help in simplifying the process of building models, especially for someone like me.
What do you dislike most about this product?
My biggest issue with this product is its lack of support for some advanced customization choices. Also, I find the pricing a bit confusing and high.
What recommendations would you give to someone considering this product?
Use the trial to test its features and gather feedback from other users to make an decision.
Pros
- Helps Innovate
- Enables Productivity
- Unique Features
- Inspires Innovation
Cons
- Less Generous
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Bharti K.
- Role: Finance
- Industry: Finance
- Involvement: Business Leader or Manager
Submitted Mar 2024
Powerful ML platform with seamless integration
Likeliness to Recommend
What differentiates Google Cloud Vertex AI from other similar products?
Google Cloud Vertex AI is distinguished by its deep integration with Google Cloud, providing a seamless experience for ML development and deployment. Its unified platform simplifies the entire ML lifecycle, offering both AutoML for quick model development and custom model training with TensorFlow for advanced users. This integration enables easy scalability and efficiency, with access to additional Google Cloud services for enhanced functionality.
What is your favorite aspect of this product?
My favorite aspect of Google Cloud Vertex AI is its seamless integration with other Google Cloud services. This integration makes it easy to leverage additional functionalities like data storage, processing, and analysis, all within the same platform. It streamlines the ML development process and allows for efficient scaling of ML workloads.
What do you dislike most about this product?
I dislike the complexity of setting up and managing ML workflows, especially for those new to machine learning. Additionally, the cost of using Google Cloud Vertex AI, especially for large-scale projects, could be a concern for some users.
What recommendations would you give to someone considering this product?
For those considering Google Cloud Vertex AI, I recommend starting with its AutoML features for easy model development. Leverage the integration with other Google Cloud services for enhanced functionality and cost-effectiveness. Be mindful of costs for large-scale projects and explore documentation for guidance. For advanced needs, utilize custom model training with TensorFlow. Scalability is a key advantage, ensuring models can grow with your business.
Pros
- Reliable
- Performance Enhancing
- Enables Productivity
- Effective Service
Cons
- Less Friendly Negotiation
- Vendor's Interest First
Please tell us why you think this review should be flagged.
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