What is TensorFlow TFX?
TFX is an end-to-end platform for deploying production ML pipelines. A TFX pipeline is a sequence of components that implement an ML pipeline which is specifically designed for scalable, high-performance machine learning tasks. Components are built using TFX libraries which can also be used individually. When you're ready to move your models from research to production, TFX can be used to create and manage a production pipeline.
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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.
90 Likeliness to Recommend
1
Since last award
100 Plan to Renew
85 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.
+93 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 TensorFlow TFX?
Pros
- Continually Improving Product
- Trustworthy
- Efficient Service
- Caring
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
Performance and Scalability
Feature Engineering
Data Labeling
Model Training
Algorithm Diversity
Model Monitoring and Management
Model Tuning
Openness and Flexibility
Ensembling
Data Pre-Processing
Data Exploration and Visualization
Vendor Capability Ratings
Quality of Features
Ease of Customization
Breadth of Features
Business Value Created
Availability and Quality of Training
Product Strategy and Rate of Improvement
Ease of IT Administration
Ease of Implementation
Ease of Data Integration
Usability and Intuitiveness
Vendor Support
TensorFlow TFX Reviews
Shaurya S.
- Role: Information Technology
- Industry: Finance
- Involvement: End User of Application
Submitted Jul 2023
Production Grade machine learning pipelines
Likeliness to Recommend
What differentiates TensorFlow TFX from other similar products?
Functional API requiring little configuration for production grade code, which is reliable and efficient.
What is your favorite aspect of this product?
Tight integration with GCP means there are additional plugins that can be used for making this.
What do you dislike most about this product?
The variety of models offered out of the box leave something to be desired.
What recommendations would you give to someone considering this product?
A good command on the open source Tensorflow library is needed for efficient usage of TFX
Pros
- Effective Service
- Appreciates Incumbent Status
- Helps Innovate
- Enables Productivity
Muskan H.
- Role: Industry Specific Role
- Industry: Engineering
- Involvement: End User of Application
Submitted Jun 2023
Production-Ready Pipelines
Likeliness to Recommend
What differentiates TensorFlow TFX from other similar products?
Some key differentiating features of TensorFlow TFX: 1. TensorFlow TFX (TensorFlow Extended) is a comprehensive platform for building and deploying production-ready machine learning (ML) pipelines. 2. TFX is specifically designed for building ML pipelines that are scalable, modular, and production-ready. It provides components for data validation, preprocessing, model training, evaluation, and serving, enabling the creation of end-to-end pipelines that can be deployed in real-world production environments.
What is your favorite aspect of this product?
TFX is a repository for managing and versioning ML models. TFX is designed to handle large-scale ML workflows efficiently.
What do you dislike most about this product?
TFX's extensive set of tools and components may introduce unnecessary complexity and overhead for smaller ML projects or experiments. Users might encounter difficulties finding detailed examples or troubleshooting specific issues related to TFX.
What recommendations would you give to someone considering this product?
TensorFlow integration, and scalable capabilities, making it an excellent choice for building end-to-end ML pipelines in real-world applications.
Pros
- Client Friendly Policies
- Helps Innovate
- Continually Improving Product
- Reliable
Habeeblahi B.
- Role: Information Technology
- Industry: Technology
- Involvement: IT Development, Integration, and Administration
Submitted Apr 2023
Easy to use, great features
Likeliness to Recommend
What differentiates TensorFlow TFX from other similar products?
TensorFlow TFX is different from other similar product due to its integration with TensorFlow which is an open-source machine learning framework and this makes it easy to leverage the vast ecosystem of TensorFlow tools, libraries, and pre-trained models.
What is your favorite aspect of this product?
My favorite aspect of TensorFlow TFX is the scalability which allows handling of large datasets and can scale to handle distributed training across multiple machines.
What do you dislike most about this product?
i have no feature i dislike in TensorFlow TFX.
What recommendations would you give to someone considering this product?
My main recommendation would be to take advantage of the TFX community. TensorFlow TFX has a large and growing community of users and developers. Take advantage of this community by joining forums, attending meetups, and asking questions.
Pros
- Helps Innovate
- Inspires Innovation
- Caring
- Altruistic
