Perpetual ML

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Perpetual ML empowers businesses with Perpetual Learning, a revolutionary technology that accelerates model training by over 100 times. It eliminates time-consuming retraining, enabling faster, more efficient model updates.
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May 31 2024
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Perpetual ML

Perpetual ML

0
0
Perpetual ML
Perpetual ML empowers businesses with Perpetual Learning, a revolutionary technology that accelerates model training by over 100 times. It eliminates time-consuming retraining, enabling faster, more efficient model updates.
Added on:
Social & Email:
Platform:
Pricing:
May 31 2024
Featured

What is Perpetual ML?

Perpetual ML is an innovative machine learning platform that leverages Perpetual Learning to significantly accelerate model training. By eliminating the time and resources typically required for retraining models, it allows businesses to achieve rapid iteration and deployment of machine learning models. The platform is designed to support diverse applications across various industries including finance, healthcare, and retail. With built-in regularization and continual learning capabilities, Perpetual ML ensures models remain up-to-date and accurate without the need for extensive manual intervention.

Who will use Perpetual ML?

  • Data Scientists
  • Machine Learning Engineers
  • Business Analysts
  • IT Managers
  • Software Developers

How to use the Perpetual ML?

  • Step1: Sign up for an account on Perpetual ML.
  • Step2: Upload your data set to the platform.
  • Step3: Configure the model training parameters.
  • Step4: Initiate the training process using Perpetual Learning.
  • Step5: Monitor training progress and performance metrics.
  • Step6: Deploy the trained model for real-time or batch predictions.
  • Step7: Utilize continual learning to keep the model updated without retraining.

Platform

  • web
  • windows
  • linux

Perpetual ML's Core Features & Benefits

The Core Features

  • Perpetual Learning
  • 100x Faster Model Training
  • Built-in Regularization
  • Automatic Continual Learning
  • Support for Multiple ML Tasks

The Benefits

  • Significant reduction in training time
  • No need for extensive retraining
  • Improved model performance and accuracy
  • Scalability across various industries
  • Ease of use and automation

Perpetual ML's Main Use Cases & Applications

  • Financial forecasting
  • Healthcare predictive analytics
  • Retail demand forecasting
  • Customer behavior modeling
  • Time series analysis

Perpetual ML's Pros & Cons

The Pros

Extremely fast initial training with PerpetualBooster technology
Supports continual learning to update models efficiently
Provides explainability and confidence intervals with advanced Conformal Prediction algorithms
Integrated model monitoring with shift detection capabilities
No need for specialized hardware, utilizing existing systems to save cost
Low-code/no-code app designed natively for modern data warehouses
Supports multiple ML tasks including tabular, time series, and text classification
Portability across multiple data warehouse platforms planned

The Cons

Currently in development for some platforms (Databricks and others) and may have limited platform support
No direct mention of user community or ecosystem size
Limited or no mention of mobile or desktop app availability
Reliance on modern data warehouses may limit use cases outside that environment

Perpetual ML's Pricing

Has free planNo
Free trial details
Pricing model
Is credit card requiredNo
Paid from
Has lifetime planNo
Billing frequency
For the latest prices, please visit: https://perpetual-ml.com/pricing

FAQs of Perpetual ML

Perpetual ML Company Information

  • Website: https://perpetual-ml.com
  • Company Name: Perpetual ML
  • Support Email: [email protected]
  • Facebook: NA
  • X(Twitter): NA
  • YouTube: NA
  • Instagram: NA
  • Tiktok: NA
  • LinkedIn: https://www.linkedin.com/company/perpetual-ml/

Perpetual ML Reviews

5/5
Do You Recommend Perpetual ML? Leave a Comment Below!

Perpetual ML's Main Competitors and alternatives?

  • Mindgrasp
  • Pinecone
  • Vertex AI
  • Amazon SageMaker
  • Microsoft Azure ML

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