From d2297c32d80fc96a37d611b5a8fa07c1cea5a763 Mon Sep 17 00:00:00 2001 From: allegroai <> Date: Tue, 22 Dec 2020 23:42:36 +0200 Subject: [PATCH] Update README.md --- README.md | 24 ++++++++++++------------ 1 file changed, 12 insertions(+), 12 deletions(-) diff --git a/README.md b/README.md index 96517a0a..0520ab59 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@
- + **ClearML - Auto-Magical Suite of tools to streamline your ML workflow @@ -20,9 +20,9 @@ Experiment Manager, ML-Ops and Data-Management** #### *Formerly known as Allegro Trains* ClearML is a ML/DL development and production suite, it contains three main modules: -- [Experiment Manager](#clearml-experiment-management) - Automagical experiment tracking, environments and results -- [ML-Ops](https://github.com/allegroai/trains-agent) - Automation, Pipelines & Orchestration solution for ML/DL jobs (K8s / Cloud / bare-metal) -- [Data-Management](https://github.com/allegroai/clearml/doc/clearml-data.md) - Fully differentiable data management & version control solution on top of object-storage +- [Experiment Manager](#clearml-experiment-manager) - Automagical experiment tracking, environments and results +- [ML-Ops](https://github.com/allegroai/clearml-agent) - Automation, Pipelines & Orchestration solution for ML/DL jobs (K8s / Cloud / bare-metal) +- [Data-Management](https://github.com/allegroai/clearml/blob/master/docs/clearml-task.md) - Fully differentiable data management & version control solution on top of object-storage (S3/GS/Azure/NAS) @@ -37,7 +37,7 @@ Instrumenting these components is the **ClearML-server**, see [Self-Hosting]() &
--- - + ## ClearML Experiment Manager @@ -58,10 +58,10 @@ Instrumenting these components is the **ClearML-server**, see [Self-Hosting]() & * Model snapshots (With optional automatic upload to central storage: Shared folder, S3, GS, Azure, Http) * Artifacts log & store (Shared folder, S3, GS, Azure, Http) * Tensorboard/TensorboardX scalars, metrics, histograms, **images, audio and video samples** - * [Matplotlib & Seaborn](https://github.com/allegroai/trains/tree/master/examples/frameworks/matplotlib) + * [Matplotlib & Seaborn](https://github.com/allegroai/clearml/tree/master/examples/frameworks/matplotlib) * [ClearML Explicit Logging](https://allegro.ai/clearml/docs/examples/reporting/) interface for complete flexibility. * Extensive platform support and integrations - * Supported ML/DL frameworks: [PyTorch](https://github.com/allegroai/trains/tree/master/examples/frameworks/pytorch)(incl' ignite/lightning), [Tensorflow](https://github.com/allegroai/trains/tree/master/examples/frameworks/tensorflow), [Keras](https://github.com/allegroai/trains/tree/master/examples/frameworks/keras), [AutoKeras](https://github.com/allegroai/trains/tree/master/examples/frameworks/autokeras), [XGBoost](https://github.com/allegroai/trains/tree/master/examples/frameworks/xgboost) and [Scikit-Learn](https://github.com/allegroai/trains/tree/master/examples/frameworks/scikit-learn) + * Supported ML/DL frameworks: [PyTorch](https://github.com/allegroai/clearml/tree/master/examples/frameworks/pytorch)(incl' ignite/lightning), [Tensorflow](https://github.com/allegroai/clearml/tree/master/examples/frameworks/tensorflow), [Keras](https://github.com/allegroai/clearml/tree/master/examples/frameworks/keras), [AutoKeras](https://github.com/allegroai/clearml/tree/master/examples/frameworks/autokeras), [XGBoost](https://github.com/allegroai/clearml/tree/master/examples/frameworks/xgboost) and [Scikit-Learn](https://github.com/allegroai/clearml/tree/master/examples/frameworks/scikit-learn) * Seamless integration (including version control) with **Jupyter Notebook** and [*PyCharm* remote debugging](https://github.com/allegroai/trains-pycharm-plugin) @@ -93,8 +93,8 @@ The ClearML run-time components: ## Additional Modules - [clearml-session](https://github.com/allegroai/clearml-session) - **Launch remote JupyterLab / VSCode-server inside any docker, on Cloud/On-Prem machines** -- [clearml-task](https://github.com/allegroai/clearml/doc/clearml-task.md) - Run any codebase on remote machines with full remote logging of Tensorboard, Matplotlib & Console outputs -- [clearml-data](https://github.com/allegroai/clearml/doc/clearml-data.md) - **CLI for managing and versioning your datasets, including creating / uploading / downloading of data from S3/GS/Azure/NAS** +- [clearml-task](https://github.com/allegroai/clearml/blob/master/docs/clearml-task.md) - Run any codebase on remote machines with full remote logging of Tensorboard, Matplotlib & Console outputs +- [clearml-data](https://github.com/allegroai/clearml/blob/master/docs/datasets.md) - **CLI for managing and versioning your datasets, including creating / uploading / downloading of data from S3/GS/Azure/NAS** - [AWS Auto-Scaler](examples/services/aws-autoscaler/aws_autoscaler.py) - Automatically spin EC2 instances based on your workloads with preconfigured budget! No need for K8s! - [Hyper-Parameter Optimization](examples/services/hyper-parameter-optimization/hyper_parameter_optimizer.py) - Optimize any code with black-box approach and state of the art Bayesian optimization algorithms - [Automation Pipeline](examples/pipeline/pipeline_controller.py) - Build pipelines based on existing experiments / jobs, supports building pipelines of pipelines! @@ -138,17 +138,17 @@ Apache License, Version 2.0 (see the [LICENSE](https://www.apache.org/licenses/L More information in the [official documentation](https://allegro.ai//clearml/docs) and [on YouTube](https://www.youtube.com/c/AllegroAI). -For examples and use cases, check the [examples folder](https://github.com/allegroai/trains/tree/master/examples) and [corresponding documentation](https://allegro.ai/clearml/docs/examples/examples_overview/). +For examples and use cases, check the [examples folder](https://github.com/allegroai/clearml/tree/master/examples) and [corresponding documentation](https://allegro.ai/clearml/docs/examples/examples_overview/). If you have any questions: post on our [Slack Channel](https://join.slack.com/t/allegroai-trains/shared_invite/enQtOTQyMTI1MzQxMzE4LTY5NTUxOTY1NmQ1MzQ5MjRhMGRhZmM4ODE5NTNjMTg2NTBlZGQzZGVkMWU3ZDg1MGE1MjQxNDEzMWU2NmVjZmY), or tag your questions on [stackoverflow](https://stackoverflow.com/questions/tagged/trains) with '**trains**' tag. -For feature requests or bug reports, please use [GitHub issues](https://github.com/allegroai/trains/issues). +For feature requests or bug reports, please use [GitHub issues](https://github.com/allegroai/clearml/issues). Additionally, you can always find us at *clearml@allegro.ai* ## Contributing -See the ClearML [Guidelines for Contributing](https://github.com/allegroai/trains/blob/master/docs/contributing.md). +See the ClearML [Guidelines for Contributing](https://github.com/allegroai/clearml/blob/master/docs/contributing.md). _May the force (and the goddess of learning rates) be with you!_