Discover top open-source software, updated regularly with real-world adoption signals.
Automated ML delivering top performance in just three lines
AutoGluon automates model selection, training, and deployment for tabular, image, text, and time‑series data, letting you build high‑accuracy models with minimal code and effort.
When teams consider AutoGluon, these hosted platforms usually appear on the same shortlist.
Cloud service for accelerating and managing the machine learning project lifecycle, including training and deployment of models
Automated machine learning platform for building AI models without coding
Unified ML platform for training, tuning, and deploying models
Looking for a hosted option? These are the services engineering teams benchmark against before choosing open source.
Customer churn prediction (tabular)
Accurately predicts churn risk, enabling targeted retention campaigns with minimal coding.
Defect detection in manufacturing images
Trains an image classifier that identifies product defects, accelerating quality control processes.
Demand forecasting for retail (time series)
Generates probabilistic forecasts to optimize inventory and supply chain decisions.
Multimodal sentiment analysis
Combines text reviews and associated images to classify sentiment, improving marketing insights.
Typically three lines: import the predictor, call fit, and call predict.
Yes, GPU support is available for deep learning models; install optional dependencies and configure the environment.
AutoGluon provides integration with SageMaker, SageMaker AutoPilot, and Docker containers for cloud deployment.
CSV files for tabular data, standard image folders, text files, and time‑series CSV/TSV formats are supported.
Yes, it is released under the Apache 2.0 license and freely available on PyPI and GitHub.
Project at a glance
ActiveLast synced 4 days ago
