Refactoring of the Getting Started page #10798
Conversation
|
Documentation preview for 5c72256 will be available here when this CircleCI job completes successfully. More info
|
github-actions
bot
added
area/docs
| @@ -9,7 +9,7 @@ how to use MLflow to solve a particular task. | |||
| Guidance on Running Tutorials | |||
| ----------------------------- | |||
|
|
|||
| If you are new to MLflow and have never interfaced with the MLflow Tracking Server, we highly encourage you to head on over to quickly read the guide below. It | |||
| If you are new to MLflow and have never interfaced with the MLflow Tracking Server, we highly encourage you to head on over to quickly **read the guide below**. It | |||
There was a problem hiding this comment.
What was the consensus on the idea of getting rid of the step for starting tracking server? The quickest way indeed is to run pip install mlflow, while the guidance ask users to some effort i.e. either signing up or setting up server. I'm afraid that mandating it will increase the mental bar for onboarding. Can we position this guide as optional step like "you can run all notebooks locally but here are the recommended set up to avoid gotchas".
There was a problem hiding this comment.
The CE / local server / managed service tracking server instructions were the defined requirements from product. I agree that fully local mode is definitely the easiest to start using the APIs, but doesn't really encourage users to adapt to the recommended interaction mode with a production deployment of MLflow.
This part of our guides isn't really available for us to change.
|
|
||
| Interested in navigating directly to the content that you're curious about? Select the section from each tutorial below! | ||
| .. figure:: ../_static/images/tutorials/introductory/autologging-intro.png |
There was a problem hiding this comment.
The center column has the strongest appearance to me, wondering if we can make it a bit less standing e.g. converting it to thin arrow rather than stacked boxes? Or even simpler showing two code boxes side-by-side.
There was a problem hiding this comment.
great idea. Updating with a more clear design.
| @@ -9,7 +9,7 @@ how to use MLflow to solve a particular task. | |||
| Guidance on Running Tutorials | |||
| ----------------------------- | |||
|
|
|||
| If you are new to MLflow and have never interfaced with the MLflow Tracking Server, we highly encourage you to head on over to quickly read the guide below. It | |||
There was a problem hiding this comment.
nit: Could you make "View the Guide to Running Tutorial Notebooks" button to inline link? We use the blue button mainly for notebook downloading, I think it's good have a single standard to reduce cognitive load.
There was a problem hiding this comment.
Switched it to a card. We definitely (per the guidance for ushering users to CE) need to make this visible.
|
|
||
| `5 Minute Tracking Server Overview <tracking-server-overview/index.html>`_ | ||
| --------------------------------------------------------------------------- | ||
| In-depth Guides |
There was a problem hiding this comment.
Can we convert this section to general "What's next?" with bullet points include tracking and other docs like LLMs, not only tutorial? Personally I like opening documents as well while running tutorials, as it helps me to understand not only bottom-up (notebooks - focus on one scenario) but also top-down (documents - explain concepts and list what are available)
Focusing on tracking in this page makes sense, but for the further path, having listing other categories of features are great like LLMs, evaluation, serving, so that users can dive deeper in their own interests.
There was a problem hiding this comment.
Great idea!! Reworked this section completely and added the lengthier guide to tracking up above in the tracking section.
| @@ -9,7 +9,7 @@ how to use MLflow to solve a particular task. | |||
| Guidance on Running Tutorials | |||
| ----------------------------- | |||
|
|
|||
| If you are new to MLflow and have never interfaced with the MLflow Tracking Server, we highly encourage you to head on over to quickly read the guide below. It | |||
| If you are new to MLflow and have never interfaced with the MLflow Tracking Server, we highly encourage you to head on over to quickly **read the guide below**. It | |||
There was a problem hiding this comment.
nit: Can we add more inline links to our technical terms like MLflow Tracking Server, MLflow fluent API? It provides answers when user faces question "what this term means?" while not needing repeating explanation.
There was a problem hiding this comment.
Added a few links where they make sense
Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com>
BenWilson2
force-pushed
the
ce-references
branch
from
b55f70d
to
521b37a
Compare
There was a problem hiding this comment.
nit: "Save Model' is missing in the left arrow?
There was a problem hiding this comment.
I guess it's because save model is automatically done by autologging?
There was a problem hiding this comment.
yeah I intentionally left it out because it's automated :)
| This quickstart tutorial focuses on the MLflow UI's run comparison feature, provides a brief overview of MLflow Projects, | ||
| and shows how to register a model. After locally serving the registered model, a brief example of preparing a model for remote deployment | ||
| via containerizing the model via Docker is covered. | ||
| This quickstart tutorial focuses on the MLflow UI's run comparison feature, provides a brief overview of `MLflow Projects <../projects.html>`_, |
There was a problem hiding this comment.
nit: this tutorial doesn't seem to mention about MLflow Project
There was a problem hiding this comment.
ooooh good catch. I totally forgot that we removed all of that from this tutorial. Thanks!
| `5 Minute Tracking Server Overview <tracking-server-overview/index.html>`_ | ||
| --------------------------------------------------------------------------- | ||
| Tracking Server Quickstart | ||
| ^^^^^^^^^^^^^^^^^^^^^^^^^^ | ||
|
|
||
| This quickstart tutorial walks through different types of MLflow Tracking Servers and how to use them to log |
There was a problem hiding this comment.
| This quickstart tutorial walks through different types of MLflow Tracking Servers and how to use them to log | |
| This quickstart tutorial walks through different types of `MLflow Tracking Servers<../tracking/server.html>`_ and how to use them to log |
There was a problem hiding this comment.
This screenshot looks a little bit vague 馃
There was a problem hiding this comment.
Agreed :) updated with some arrows and boxes to explain what the image really is
Signed-off-by: Ben Wilson <benjamin.wilson@databricks.com>
馃洜 DevTools 馃洜
Install mlflow from this PR
Checkout with GitHub CLI
Related Issues/PRs
#xxxWhat changes are proposed in this pull request?
Cleanup and streamline the getting started with MLflow page. Removed a useless tutorial and collapsed sections into a cleaner and less cluttered design.
How is this PR tested?
Does this PR require documentation update?
Release Notes
Is this a user-facing change?
Overhauled the getting started with MLflow page.
What component(s), interfaces, languages, and integrations does this PR affect?
Components
area/artifacts: Artifact stores and artifact loggingarea/build: Build and test infrastructure for MLflowarea/deployments: MLflow Deployments client APIs, server, and third-party Deployments integrationsarea/docs: MLflow documentation pagesarea/examples: Example codearea/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models: MLmodel format, model serialization/deserialization, flavorsarea/recipes: Recipes, Recipe APIs, Recipe configs, Recipe Templatesarea/projects: MLproject format, project running backendsarea/scoring: MLflow Model server, model deployment tools, Spark UDFsarea/server-infra: MLflow Tracking server backendarea/tracking: Tracking Service, tracking client APIs, autologgingInterface
area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/docker: Docker use across MLflow's components, such as MLflow Projects and MLflow Modelsarea/sqlalchemy: Use of SQLAlchemy in the Tracking Service or Model Registryarea/windows: Windows supportLanguage
language/r: R APIs and clientslanguage/java: Java APIs and clientslanguage/new: Proposals for new client languagesIntegrations
integrations/azure: Azure and Azure ML integrationsintegrations/sagemaker: SageMaker integrationsintegrations/databricks: Databricks integrationsHow should the PR be classified in the release notes? Choose one:
rn/none- No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" sectionrn/breaking-change- The PR will be mentioned in the "Breaking Changes" sectionrn/feature- A new user-facing feature worth mentioning in the release notesrn/bug-fix- A user-facing bug fix worth mentioning in the release notesrn/documentation- A user-facing documentation change worth mentioning in the release notes