Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
The Kubeflow initiative aims to simplify the process of deploying machine learning workflows on Kubernetes, ensuring they are both portable and scalable. Rather than duplicating existing services, our focus is on offering an easy-to-use platform for implementing top-tier open-source ML systems across various infrastructures. Kubeflow is designed to operate seamlessly wherever Kubernetes is running. It features a specialized TensorFlow training job operator that facilitates the training of machine learning models, particularly excelling in managing distributed TensorFlow training tasks. Users can fine-tune the training controller to utilize either CPUs or GPUs, adapting it to different cluster configurations. In addition, Kubeflow provides functionalities to create and oversee interactive Jupyter notebooks, allowing for tailored deployments and resource allocation specific to data science tasks. You can test and refine your workflows locally before transitioning them to a cloud environment whenever you are prepared. This flexibility empowers data scientists to iterate efficiently, ensuring that their models are robust and ready for production.
Description
Fusion transforms siloed data into unique insights for each user. Lucidworks Fusion allows customers to easily deploy AI-powered search and data discovery applications in a modern, containerized cloud-native architecture. Data scientists can interact with these applications by using existing machine learning models. They can also quickly create and deploy new models with popular tools such as Python ML and TensorFlow. It is easier and less risk to manage Fusion cloud deployments. Lucidworks has modernized Fusion using a cloud-native microservices architecture orchestrated and managed by Kubernetes. Fusion allows customers to dynamically manage their application resources according to usage ebbs, flows, and reduce the effort of deploying Fusion and upgrading it. Fusion also helps avoid unscheduled downtime or performance degradation. Fusion supports Python machine learning models natively. Fusion can integrate your custom ML models.
API Access
Has API
No
API Access
Has API
No
Integrations
APERIO DataWise
Yes
Azure Marketplace
Yes
Camunda
Yes
Canopy
No
Civo
Yes
Comet LLM
Yes
D2iQ
Yes
DagsHub
Yes
FindTuner
No
Flyte
Yes
Integrations
APERIO DataWise
No
Azure Marketplace
No
Camunda
No
Canopy
Yes
Civo
No
Comet LLM
No
D2iQ
No
DagsHub
No
FindTuner
Yes
Flyte
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
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
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
Yes
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Kubeflow
Website
www.kubeflow.org
Vendor Details
Company Name
Lucidworks
Founded
2007
Country
United States
Website
lucidworks.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
eCommerce Personalization
A/B Testing
No
Abandoned Cart Email
No
Dynamic Pricing
No
Offers & Discounts Notifications
No
Personalized Site Navigation
No
Product Recommendations
No
Reporting / Analytics
No
Social Insights
No
Enterprise Search
AI / Machine Learning
Yes
Faceted Search / Filtering
No
Full Text Search
Yes
Fuzzy Search
No
Indexing
Yes
Text Analytics
No
eDiscovery
No
Insight Engines
AI / Machine Learning
No
Augmented Analytics
No
Data Aggregation
No
Data Classification
No
Data Extraction
No
Data Source Connectors
No
Full Text Search
No
Intent Recognition
No
Multiple Data Sources
No
Search / Filter
No
Sentiment Analysis
No