perpetual-ml.com

What is Perpetual ML?

Perpetual ML is a cutting-edge suite designed for modern data warehouses, offering a ### 100x faster, scalable, explainable, end-to-end solution. This low-code/no-code application allows businesses to uncover insights and take action on their data in minutes, rather than days.

What are the main features of Perpetual ML?

100x Faster Initial Training: The PerpetualBooster enables initial training of models 100 times faster, thanks to its built-in generalization algorithm which eliminates the need for extensive hyperparameter optimization.
Continual Learning: Users can continuously train their models from where they left off, ensuring efficiency without the need to restart from scratch with each new data batch.
Enhanced Decision-Making: The platform offers better confidence intervals utilizing state-of-the-art Conformal Prediction algorithms, enhancing decision-making capabilities over standard implementations.
Geographic Data Learning: Perpetual ML improves learning of decision boundaries for geographic data, making it more relevant for location-specific analyses.
Model Monitoring: Users benefit from built-in tools to monitor models and confidently detect distribution shifts, eliminating the need for additional monitoring tools.
Versatile ML Tasks: The suite accommodates a range of tasks including tabular classification, regression, time series analysis, learning to rank, and text classification using embeddings.
Portability: Designed to avoid vendor lock-in, Perpetual ML is currently optimized for Snowflake with plans for expansion to Databricks and other data warehouses.
Effortless Parallelism: The platform enhances computational performance and resource efficiency, boosting the potential of research and applications.
No Specialized Hardware Needed: Perpetual ML can be run on standard hardware setups, eliminating the complexity and cost of specialized GPU or TPU systems.

How to use Perpetual ML?

Utilizing Perpetual ML is straightforward. Businesses can request a free trial to experience the suite in action and evaluate its capabilities in relation to their specific data processing and analytical needs.

What is the pricing structure for Perpetual ML?

Perpetual ML offers a competitive pricing structure designed to cater to various business needs. For detailed pricing information, potential users are encouraged to contact Perpetual ML directly for tailored options and insights.

Helpful Tips for Maximizing Perpetual ML Usage

Take advantage of the free trials to explore the various features before committing.
Ensure your data is organized and clean to maximize the effectiveness of model training.
Regularly monitor your models to detect shifts in data distribution early.
Leverage the low-code features to engage non-technical users in data analysis.

Frequently Asked Questions

Can I integrate Perpetual ML with my existing data infrastructure?

Yes, Perpetual ML is designed for compatibility with modern data warehouses like Snowflake, and it will soon support others such as Databricks.

Is there a need for specialized hardware to run Perpetual ML?

No, Perpetual ML is designed to function effectively on standard hardware, saving costs and avoiding hardware complexity.

What types of machine learning tasks can I run with Perpetual ML?

The suite is suited for various ML tasks, including classification, regression, time series analysis, and more, making it versatile for different industries.

How does Perpetual ML ensure better decision-making?

By employing advanced algorithms like Conformal Prediction, Perpetual ML provides improved confidence intervals, leading to more reliable decision-making processes.

How can I get support if I have questions about using Perpetual ML?

For any support or inquiries, you can contact Perpetual ML directly for assistance and guidance tailored to your unique requirements.

perpetual-ml.com Home Page

Introduction

What is Perpetual ML?

What are the main features of Perpetual ML?

100x Faster Initial Training: The PerpetualBooster enables initial training of models 100 times faster, thanks to its built-in generalization algorithm which eliminates the need for extensive hyperparameter optimization.

Continual Learning: Users can continuously train their models from where they left off, ensuring efficiency without the need to restart from scratch with each new data batch.

Enhanced Decision-Making: The platform offers better confidence intervals utilizing state-of-the-art Conformal Prediction algorithms, enhancing decision-making capabilities over standard implementations.

Geographic Data Learning: Perpetual ML improves learning of decision boundaries for geographic data, making it more relevant for location-specific analyses.

Model Monitoring: Users benefit from built-in tools to monitor models and confidently detect distribution shifts, eliminating the need for additional monitoring tools.

Versatile ML Tasks: The suite accommodates a range of tasks including tabular classification, regression, time series analysis, learning to rank, and text classification using embeddings.

Portability: Designed to avoid vendor lock-in, Perpetual ML is currently optimized for Snowflake with plans for expansion to Databricks and other data warehouses.

Effortless Parallelism: The platform enhances computational performance and resource efficiency, boosting the potential of research and applications.

No Specialized Hardware Needed: Perpetual ML can be run on standard hardware setups, eliminating the complexity and cost of specialized GPU or TPU systems.