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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Create continuously improving predictive models effortlessly, without the need for intricate engineering processes. Seamlessly integrate with your current cloud data warehouse, utilizing all available data in its existing location. Effortlessly share features and deploy advanced machine learning models using just SQL or dbt, or expand functionality with Python if needed. Keep predictions organized within your data warehouse for straightforward access by your business intelligence and operational systems. Manage features and predictions directly in your data warehouse, eliminating the need for additional infrastructure. Construct cutting-edge models that capitalize on all your data without the necessity of writing code or establishing pipelines. Foster collaboration between analytics and AI teams through the comprehensive extensibility of Continual's declarative AI framework. Oversee features, models, and policies using a declarative GitOps workflow as your operations expand. Enhance the speed of model development with a collaborative feature store and a data-centric approach, while also ensuring cross-team communication remains seamless. This innovative approach allows for a more integrated and efficient workflow, ultimately driving better insights and outcomes.

Description

Ludwig serves as a low-code platform specifically designed for the development of tailored AI models, including large language models (LLMs) and various deep neural networks. With Ludwig, creating custom models becomes a straightforward task; you only need a simple declarative YAML configuration file to train an advanced LLM using your own data. It offers comprehensive support for learning across multiple tasks and modalities. The framework includes thorough configuration validation to identify invalid parameter combinations and avert potential runtime errors. Engineered for scalability and performance, it features automatic batch size determination, distributed training capabilities (including DDP and DeepSpeed), parameter-efficient fine-tuning (PEFT), 4-bit quantization (QLoRA), and the ability to handle larger-than-memory datasets. Users enjoy expert-level control, allowing them to manage every aspect of their models, including activation functions. Additionally, Ludwig facilitates hyperparameter optimization, offers insights into explainability, and provides detailed metric visualizations. Its modular and extensible architecture enables users to experiment with various model designs, tasks, features, and modalities with minimal adjustments in the configuration, making it feel like a set of building blocks for deep learning innovations. Ultimately, Ludwig empowers developers to push the boundaries of AI model creation while maintaining ease of use.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Aim No 
Alpaca No 
Amazon Redshift Yes 
Comet No 
Databricks Yes 
Discord No 
Docker No 
Google Cloud BigQuery Yes 
Hugging Face No 
Kubernetes No 
Llama 2 No 
MLflow No 
Python No 
RAY No 
Snowflake Yes 
TensorBoard No 
Triton No 
Weights & Biases No 

Integrations

Aim Yes 
Alpaca Yes 
Amazon Redshift No 
Comet Yes 
Databricks No 
Discord Yes 
Docker Yes 
Google Cloud BigQuery No 
Hugging Face Yes 
Kubernetes Yes 
Llama 2 Yes 
MLflow Yes 
Python Yes 
RAY Yes 
Snowflake No 
TensorBoard Yes 
Triton Yes 
Weights & Biases Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
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 No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux Yes 
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 No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Continual

Founded

2019

Country

United States

Website

continual.ai/

Vendor Details

Company Name

Uber AI

Founded

2016

Country

United States

Website

ludwig.ai/latest/

Product Features

Artificial Intelligence

Chatbot No 
For Healthcare No 
For Sales No 
For eCommerce No 
Image Recognition No 
Machine Learning No 
Multi-Language No 
Natural Language Processing No 
Predictive Analytics No 
Process/Workflow Automation No 
Rules-Based Automation No 
Virtual Personal Assistant (VPA) No 

Predictive Analytics

AI / Machine Learning No 
Benchmarking No 
Data Blending No 
Data Mining No 
Demand Forecasting No 
For Education No 
For Healthcare No 
Modeling & Simulation No 
Sentiment Analysis No 

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 

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