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llog

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About

llog.ai is an AI-powered tool designed to streamline ML experiments. It offers end-to-end experiment lifecycle management, from templatized config setup using YAML files or argparse code, to visual modification via a web GUI, and no-code visualization of results. llog supports launching experiments on your server or via SLURM, features version control for reproducibility and collaboration, and allows for one-click addition of new parameters across pipelines. It aims to reduce the software engineering burden for ML researchers by automating repetitive tasks and providing AI-driven insights into data and pipeline performance, including predictive analytics.

Platform
Web
Keywords
aimanagementmlexperimentslifecycle
Task
ml experimentation

Features

version control

templatized configs

automated visualizations

work with your infrastructure

adding parameters

experiment launching

visualize results

web gui

FAQs

What is llog? Why do I need it?

llog helps ML research scientists set up, launch and reproduce their experiments. You don't \*need\* it but wouldn't it be a whole lot cooler if you had a nice GUI to set your hyperparameters, make experiment modifications visually & support launching experiments in one click.

How does LLog determine how to merge data? Can I customize the merging logic?

The AI analyzes snapshots of your data across tables, identifies the type of each column and finds common keys. If multiple merge options exist, llog will identify which join runs the most efficiently. Users can manually audit the join rules & parameters.

What metrics are used to measure pipeline performance?

Throughput, latency, publish frequency are some of the metrics we use to measure pipeline performance.

Is there support for predictive analytics to prevent future anomalies?

llog offers predictive analytics and load testing to forecast potential issues & breaking points for your pipeline.

Can I customize the thresholds for what is considered an anomaly?

Of course! Performance thresholds, anomaly detection and incident reporting can be customized based on your needs.

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