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HPE Machine Learning OPS
Houston, USA
1939
$10BN to $50BN
Enterprise
94 Likes
66 Buyers Negotiating

Summary

Following features are offered by HPE ML Ops solution-
  • Model Build- Offers Pre-packaged, self-service sandbox environments for ML tools and data science notebooks
  • Model Training- Provides scalable training environments with secure access to data
  • Model Deployment- Enables flexible and rapid deployment with reproducibility
  • Model Monitoring- Monitors end-to-end visibility across the ML model lifecycle
  • Collaboration- Enables CI/CD workflows with code, model, and project repositories
  • Security and Control- Secure multi-tenancy with integration to enterprise authentication mechanisms
  • Hybrid Deployment- Supports for on-premises, public cloud, or hybrid cloud


Pricing:

The company had not disclosed the price structure for its Machine Learning solution. For detailed HPE ML Ops pricing, please contact HPE through its website.

 

Free Demo:

For further details on free demo for HPE ML Ops, we recommend that you visit the company’s website.

Discussions

Strengths
  • +9
    Platform
  • +10
    Services
  • +8
    Software Tools
  • +6
    APIs for Batch and Real-time Predictions
  • +7
    Data Transformations
  • +11
    Data visualization and exploration
  • +14
    Machine Learning Algorithms
  • +5
    Model assessment and scoring
  • +12
    Model Evaluation and Interpretation Tools
  • +13
    Modeling APIs
  • +10
    Customer Support
  • +6
    Dedicated Account Manager (DAM)
  • +14
    Product Demos
  • +5
    Proof of Concept
  • +11
    Sales Support
  • +13
    Software Requirement Specification (SRS)
  • +9
    Technical Support
  • +10
    Product Features and Functionality
  • +7
    Solution Scalability
  • +8
    licenses
Cautions
  • -10
    Large Enterprises (Revenue> 500 Million)
  • -8
    Managed services (Support & Maintenance)
  • -7
    Professional Services (Consulting & Training)
  • -9
    Small and Medium sized Enterprise
  • -11
    Product Upgradation
  • -9
    Breadth and Depth of Product Offerings
  • -7
    On-Site Support
  • -12
    Product Differentiation and Impact on Customer Value
  • -13
    Product Quality and Reliability
  • -8
    Remote Support
  • -6
    Customer Feedback Frequency
  • -12
    Product Innovation
  • -12
    New Product Launches
  • -11
    cutomer satisfaction
  • -14
    R&D Spend
  • -6
    Customer Redressal Mechanism/Program
  • -5
    Level of Support
  • -11
    Focus on Product Innovation
  • -12
    Others, please specify
HPE Machine Learning OPS Presence in Machine Learning Software
HPE has a product portfolio that specifically focuses on various business and IT operations, such as finance, marketing, sales, and operations. It has expanded its portfolio rapidly and is making moves to expand further to address increasing customer demand for standards-based software that will help automate business processes with the help of mobility devices. HPE products are instrumental in achieving high operational excellence, fast-track time-to-market, optimizing asset utilization, and reducing costs to improve efficiency. On the grounds of machine learning, HPE is following an organic strategy with various product upgradations. In August 2016, the company upgraded its HPE Haven OnDemand platform with Haven OnDemand Combinations, which empowers developers to utilize the power of best machine learning software to develop next generation applications. In line with the inorganic growth strategy, in February 2017, HPE acquired SGI, one of the leading providers of highperformance solutions for computing, data analytics, and data management. The acquisition strengthened HPE’s position in the server market by incorporating SGI’s complementary product portfolio.
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Company Size :
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  SME
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