Integrate GradientCI in Slack
with Axolo

GradientCI is a powerful GitHub application that enables teams to build reproducible, maintainable, and deterministic machine learning models. The service runs machine learning models in every pull request or commit and reports back model and host metrics, allowing teams to track metrics such as loss and accuracy, CPU/GPU utilization, and training time.

With built-in integrations for TensorFlow model parsing, GradientCI adds valuable insights directly into your code, making it easier to develop and deploy machine learning models with ease. The service supports GCP/AWS/Azure/ and on-premise installations, giving teams the flexibility to choose the cloud provider that best fits their needs.

GradientCI is designed to help teams create continuously updated machine learning models with triggers for model/data drift, enabling them to build sophisticated ML pipelines. The service is free for OSS, making it an excellent choice for academics, researchers, students, and more to build their models with FREE GPU time.

Overall, GradientCI is a modern MLOps platform that enables teams to continuously develop and deploy machine learning models with ease. Whether you're building models for research, education, or production, GradientCI makes it easy to track metrics, reproduce results, and deploy models into production.

List of GradientCI features:
1. Runs machine learning models in every pull request or commit
2. Reports back model and host metrics
3. Supports GCP/AWS/Azure/ and on-premise installations
4. Built-in integrations for TensorFlow model parsing
5. Reproducible Machine Learning
6. Run any model and report back model performance metrics
7. Status checks to confirm model performance before merging to master or deploying into production
8. Track metrics such as Loss and Accuracy, CPU/GPU utilization, Training time
9. Modern MLOps
10. Continuously develop and deploy machine learning models with ease
11. Easily pass custom model data for any framework of your choosing
12. Train / Evaluate / Deploy
13. Create continuously updated machine learning models
14. Triggers for model/data drift to build sophisticated ML pipelines
15. Free for OSS
16. Dynamically scale up deployments from single-node CPU to large-scale distributed GPU tasks
17. Hosted solution or run in public cloud VPC or on-prem.

The pricing for GradientCI's community use is free, at $0.

Integrating GradientCI with Axolo in Slack can help engineers review code faster and more efficiently by providing valuable insights into model performance metrics directly within the code review process. This can help ensure that machine learning models perform as expected before merging to master or deploying them into production, ultimately leading to more reproducible, maintainable, and deterministic models.