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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Deploy your machine learning model in the cloud within minutes using a consolidated packaging format that supports both online and offline operations across various platforms. Experience a performance boost with throughput that is 100 times greater than traditional flask-based model servers, achieved through our innovative micro-batching technique. Provide exceptional prediction services that align seamlessly with DevOps practices and integrate effortlessly with widely-used infrastructure tools. The unified deployment format ensures high-performance model serving while incorporating best practices for DevOps. This service utilizes the BERT model, which has been trained with the TensorFlow framework to effectively gauge the sentiment of movie reviews. Our BentoML workflow eliminates the need for DevOps expertise, automating everything from prediction service registration to deployment and endpoint monitoring, all set up effortlessly for your team. This creates a robust environment for managing substantial ML workloads in production. Ensure that all models, deployments, and updates are easily accessible and maintain control over access through SSO, RBAC, client authentication, and detailed auditing logs, thereby enhancing both security and transparency within your operations. With these features, your machine learning deployment process becomes more efficient and manageable than ever before.

Description

Declarative machine learning systems offer an ideal combination of flexibility and ease of use, facilitating the rapid implementation of cutting-edge models. Users concentrate on defining the “what” while the system autonomously determines the “how.” Though you can start with intelligent defaults, you have the freedom to adjust parameters extensively, even diving into code if necessary. Our team has been at the forefront of developing declarative machine learning systems in the industry, exemplified by Ludwig at Uber and Overton at Apple. Enjoy a selection of prebuilt data connectors designed for seamless compatibility with your databases, data warehouses, lakehouses, and object storage solutions. This approach allows you to train advanced deep learning models without the hassle of infrastructure management. Automated Machine Learning achieves a perfect equilibrium between flexibility and control, all while maintaining a declarative structure. By adopting this declarative method, you can finally train and deploy models at the speed you desire, enhancing productivity and innovation in your projects. The ease of use encourages experimentation, making it easier to refine models based on your specific needs.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

AWS Lambda Yes 
Amazon Redshift No 
Amazon SageMaker Yes 
Amazon Web Services (AWS) Yes 
Apache Airflow Yes 
Azure Container Registry Yes 
Azure Functions Yes 
Docker Yes 
Google Cloud Run Yes 
Google Compute Engine Yes 
Grafana Cloud Yes 
H2O.ai Yes 
Knative Yes 
MySQL No 
NVIDIA DRIVE Yes 
Opik No 
Prometheus Yes 
PyTorch Yes 
Python No 
Snowflake No 

Integrations

AWS Lambda No 
Amazon Redshift Yes 
Amazon SageMaker No 
Amazon Web Services (AWS) No 
Apache Airflow No 
Azure Container Registry No 
Azure Functions No 
Docker No 
Google Cloud Run No 
Google Compute Engine No 
Grafana Cloud No 
H2O.ai No 
Knative No 
MySQL Yes 
NVIDIA DRIVE No 
Opik Yes 
Prometheus No 
PyTorch No 
Python Yes 
Snowflake Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

Pay-as-you-go pricing
Free Trial Yes 
Free Version No 

Deployment

Web-Based No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Vendor Details

Company Name

BentoML

Country

United States

Website

www.bentoml.com

Vendor Details

Company Name

Predibase

Country

United States

Website

predibase.com

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Product Features

Machine Learning

Deep Learning No 
ML Algorithm Library No 
Model Training No 
Natural Language Processing (NLP) No 
Predictive Modeling No 
Statistical / Mathematical Tools No 
Templates No 
Visualization No 

Alternatives

Alternatives