Perpetual ML - 100x faster, scalable, all-in-one ML Suite for modern data warehouses

Perpetual ML 100x faster, scalable, all-in-one ML Suite for modern data warehouses

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#Machine Learning
#data warehouse
#model monitoring
#Continuous learning
#parallel computing
#snowflake

What is Perpetual ML?

Perpetual ML Suite is a revolutionary machine learning platform that delivers unprecedented speed and efficiency for businesses utilizing modern data warehouses. The platform's standout feature is its PerpetualBooster technology, which achieves 100x faster initial training through an innovative generalization algorithm that eliminates the need for hyperparameter optimization.

The suite offers comprehensive functionality including continual learning capabilities, advanced geographic data processing, and built-in state-of-the-art Conformal Prediction algorithms for better confidence intervals. Operating without specialized hardware requirements, it provides seamless model monitoring, effortless parallelism, and supports various ML tasks including tabular classification, regression, time series analysis, and text classification.

Features

PerpetualBooster: 100x faster initial training with built-in generalization algorithm
Continual Learning: Continuous model training without starting from scratch
Conformal Prediction: Advanced algorithms for better confidence intervals
Geographic Learning: Enhanced processing of geographic data
Model Monitoring: Built-in monitoring and distribution shift detection
Hardware Flexibility: No specialized hardware requirements
Multi-task Support: Handles classification, regression, time series, and text classification
Effortless Parallelism: Superior computational performance and resource efficiency

Use Cases

Data warehouse machine learning optimization
Continuous model training and updating
Geographic data analysis
Time series prediction
Text classification using embeddings
Model performance monitoring
Resource-efficient ML deployment

FAQs

What types of ML tasks does Perpetual ML support?

Perpetual ML supports tabular classification, regression, time series, learning to rank tasks, and text classification using embeddings.
Which data warehouse platforms are supported?

Currently, it is being developed for Snowflake, with plans to expand to Databricks and other data warehouses in the future.
Do I need specialized hardware like GPUs to run Perpetual ML?

No, Perpetual ML does not require specialized hardware like GPU or TPU, allowing you to leverage your current hardware and software infrastructure.