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FREE TRIAL OF DOMINO MODEL MONITOR Detect problems before they cause serious business impact. Domino Model Monitor creates a “single pane of glass” to monitor the performance of all models across your entire organization. You can focus on value-added data science projects and receive alerts when production models degrade. Quickly analyze data drift and modelquality using an
INSTALLING PACKAGES AND DEPENDENCIES R¶. If you’re using Domino for R scripts, you may also want to check out our R Package for controlling Domino in your R IDE.. Most common packages are installed by default (you can include installed.packages() at the start of your script to print out a list of installed packages). If you need additional packages, you can use R’s built-in package manager to install and load them: simply APPLYING LEADING-EDGE DATA SCIENCE TO PUSH THE BOUNDS OFSEE MORE ONDOMINODATALAB.COM
CLUSTER REQUIREMENTS Native¶. For shared storage, we allow for (and even require) native cloud provider object store for a few resources and services: Blob Storage.For AWS, the blob storage must be backed by S3 (see Blob storage).For other infrastructure, the dominoshared storage class isused.. Logs.
GIT REPOSITORIES IN DOMINO Overview. Domino supports adding Git repositories to projects. Repositories that have been added to a project are available to Runs started in that project, allowing you to access the contents of those repositories just as you would your Domino files. BUILDING INTERACTIVE DASHBOARDS WITH JUPYTER The first argument is the function that handles the selected value of the second argument. The type of second argument will decide the form of the interaction. As you can see: an integer results in a slider. Giving a boolean ( interact (f, x=True)) creates a checkbox. You can store widgets in variables in your notebook just like any other type THE ENTERPRISE MLOPS PLATFORM Domino’s enterprise MLOps platform accelerates research, speeds model deployment, and increases collaboration for code-first data science teams at scale. Explore the platform. slide 8 to 12 of 13. DATA SCIENCE PRODUCT FOR THE FULL LIFECYCLE Domino is the enterprise data science management platform - where data science work gets done across Data Scientists, IT, and Technical Leaders. Data Science is hard, given constantly changing technologies, burdensome infrastructure requirements across IT, and governance needs DOMINO DATA LAB AT NVIDIA GTC 2021 For AI Innovators and Technology Leaders: Attend NVIDIA GTC 2021 April 12-16, 2021. Learn how enterprise MLOps can help you achieve model velocity. Win a jet ski by tuning into these free sessions! Brought to you by Domino Data Lab. ENVIRONMENT MANAGEMENT Environment management is the practice of creating new Domino environments and editing existing environments to meet your specific language and package needs. This work is typically done by an administrator or advanced Domino user. Here are some examples of whento create or
FREE TRIAL OF DOMINO MODEL MONITOR Detect problems before they cause serious business impact. Domino Model Monitor creates a “single pane of glass” to monitor the performance of all models across your entire organization. You can focus on value-added data science projects and receive alerts when production models degrade. Quickly analyze data drift and modelquality using an
INSTALLING PACKAGES AND DEPENDENCIES R¶. If you’re using Domino for R scripts, you may also want to check out our R Package for controlling Domino in your R IDE.. Most common packages are installed by default (you can include installed.packages() at the start of your script to print out a list of installed packages). If you need additional packages, you can use R’s built-in package manager to install and load them: simply APPLYING LEADING-EDGE DATA SCIENCE TO PUSH THE BOUNDS OFSEE MORE ONDOMINODATALAB.COM
CLUSTER REQUIREMENTS Native¶. For shared storage, we allow for (and even require) native cloud provider object store for a few resources and services: Blob Storage.For AWS, the blob storage must be backed by S3 (see Blob storage).For other infrastructure, the dominoshared storage class isused.. Logs.
GIT REPOSITORIES IN DOMINO Overview. Domino supports adding Git repositories to projects. Repositories that have been added to a project are available to Runs started in that project, allowing you to access the contents of those repositories just as you would your Domino files. BUILDING INTERACTIVE DASHBOARDS WITH JUPYTER The first argument is the function that handles the selected value of the second argument. The type of second argument will decide the form of the interaction. As you can see: an integer results in a slider. Giving a boolean ( interact (f, x=True)) creates a checkbox. You can store widgets in variables in your notebook just like any other type DATA SCIENCE PRODUCT FOR THE FULL LIFECYCLE Domino is the enterprise data science management platform - where data science work gets done across Data Scientists, IT, and Technical Leaders. Data Science is hard, given constantly changing technologies, burdensome infrastructure requirements across IT, and governance needs BIOINFORMATICS AND THE UNPRECEDENTED COVID-19 VACCINE RACE Fiona Hyland, Director of R&D, DNA Sequencing Informatics at Thermo Fisher Scientific, joins host Dave Cole to discuss the field of bioinformatics and its critical role in medical breakthroughs like the COVID-19 vaccine. Listen to Data Science Leaders, a podcast fromDomino Data Lab.
CLOUD DATA SCIENCE
A data science workbench on machines of your choosing. Modern data science techniques depend on powerful CPUs and GPUs. The demand is lumpy, leading to idle resources and wasted costs. Domino lets data scientists spin up large or specialized hardware with one click, pre-configured with the tools they already use (e.g., R, Python,Jupyter).
SNOWFLAKE DATA CLOUD Reduce silos and create a research flywheel. Data science teams can find and build on past work and freely collaborate with their peers to not only unlock new ideas and breakthrough insights, but share them across business stakeholders through Snowflake, ensuring simultaneous access with the elasticity of Snowflake’s Data Cloud. JUPYTER | DOMINO DATA LAB Do Less DevOps and More Data Science Jupyter is a great tool for data science, and Domino lets you get the most out of it. Domino automatically tracks changes to your notebooks and experiments—code, data, results, and environment—so you can always revert or reproduce old results, and even compare how your notebooks and results havechanged over time.
THE PRACTICAL GUIDE TO MANAGING DATA SCIENCE AT SCALE Lessons from the field on managing data science projects and portfolios. The ability to manage, scale, and accelerate an entire data science discipline increasingly separates successful organizations from those falling victim to hype and disillusionment.INSTALLATION
Private or offline installation. Downloading. Extracting and loading. Installing. Configuration. fleetcommand-agent release notes. fleetcommand-agent v37 (March 2021) fleetcommand-agent v34 (February 2021) fleetcommand-agent v33 (February 2021) CLUSTER REQUIREMENTS Native¶. For shared storage, we allow for (and even require) native cloud provider object store for a few resources and services: Blob Storage.For AWS, the blob storage must be backed by S3 (see Blob storage).For other infrastructure, the dominoshared storage class isused.. Logs.
WORKSPACES — DOMINO DOCS 4.4 DOCUMENTATION Overview¶. A Domino workspace is an interactive session where you can conduct research, analyze data, train models, and more. Workspaces enable you to work in a development environment of your choice, like Jupyter notebooks, RStudio, VS Code, and many other customizableenvironments.
MODEL INTERPRETABILITY WITH TCAV (TESTING WITH CONCEPT This Domino Data Science Field Note provides very distilled insights and excerpts from Been Kim’s recent MLConf 2018 talk and research about Testing with Concept Activation Vectors (TCAV), an interpretability method that allows researchers to understand and quantitatively measure the high-level concepts their neural network models are using for prediction, “even if the concept was not THE ENTERPRISE MLOPS PLATFORM Domino’s enterprise MLOps platform accelerates research, speeds model deployment, and increases collaboration for code-first data science teams at scale. Explore the platform. slide 8 to 12 of 13.MACHINE LEARNING
Machine learning (ML) is the application of computer algorithms that improve automatically through experience. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmedto do so.
JUPYTER | DOMINO DATA LAB Do Less DevOps and More Data Science Jupyter is a great tool for data science, and Domino lets you get the most out of it. Domino automatically tracks changes to your notebooks and experiments—code, data, results, and environment—so you can always revert or reproduce old results, and even compare how your notebooks and results havechanged over time.
MODEL MONITORING BEST PRACTICES Model monitoring is a vital operational task that allows you to check that your models are performing to the best of their abilities. In addition to providing recommendations for establishing best practices for model monitoring, Model Monitoring Best Practices: Maintaining Data Science at Scale, offers advice on how to estimate its impact ENVIRONMENT MANAGEMENT Environment management is the practice of creating new Domino environments and editing existing environments to meet your specific language and package needs. This work is typically done by an administrator or advanced Domino user. Here are some examples of whento create or
INSTALLING PACKAGES AND DEPENDENCIES R¶. If you’re using Domino for R scripts, you may also want to check out our R Package for controlling Domino in your R IDE.. Most common packages are installed by default (you can include installed.packages() at the start of your script to print out a list of installed packages). If you need additional packages, you can use R’s built-in package manager to install and load them: simply USE THE DOMINO COMMAND LINE INTERFACE (CLI) Use the Domino command line interface (CLI) ¶. Use the Domino command line interface (CLI) ¶. Installing the Domino Command Line (CLI) CLI reference. Downloading files with the CLI. Force restoring a local project. How to move a project from one Domino deployment to another. Using the CLI behind a GIT REPOSITORIES IN DOMINO Overview ¶. Domino supports adding Git repositories to projects. Repositories that have been added to a project are available to Runs started in that project, allowing you to access the contents of those repositories just as you would your Domino files. DOWNLOADING INDIVIDUAL FILES OR FOLDERS WITH THE CLI Downloading individual files or folders with the CLI. If you need to download individual files from a project, the simplest way to do this is from the Files page in the UI. However, if your files are too numerous to manage from the UI, there is an alternate method using a CLI command: domino download-results. This command accepts a filterthat
GETTING STARTED WITH FLASK Getting started with Flask¶. The following guide will set up your Domino project more as a proper web site powered by Flask. This isn’t difficult; you just need to make sure all the folders and files are in place to ensure the app runs correctly. THE ENTERPRISE MLOPS PLATFORM Domino’s enterprise MLOps platform accelerates research, speeds model deployment, and increases collaboration for code-first data science teams at scale. Explore the platform. slide 8 to 12 of 13.MACHINE LEARNING
Machine learning (ML) is the application of computer algorithms that improve automatically through experience. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmedto do so.
JUPYTER | DOMINO DATA LAB Do Less DevOps and More Data Science Jupyter is a great tool for data science, and Domino lets you get the most out of it. Domino automatically tracks changes to your notebooks and experiments—code, data, results, and environment—so you can always revert or reproduce old results, and even compare how your notebooks and results havechanged over time.
MODEL MONITORING BEST PRACTICES Model monitoring is a vital operational task that allows you to check that your models are performing to the best of their abilities. In addition to providing recommendations for establishing best practices for model monitoring, Model Monitoring Best Practices: Maintaining Data Science at Scale, offers advice on how to estimate its impact ENVIRONMENT MANAGEMENT Environment management is the practice of creating new Domino environments and editing existing environments to meet your specific language and package needs. This work is typically done by an administrator or advanced Domino user. Here are some examples of whento create or
INSTALLING PACKAGES AND DEPENDENCIES R¶. If you’re using Domino for R scripts, you may also want to check out our R Package for controlling Domino in your R IDE.. Most common packages are installed by default (you can include installed.packages() at the start of your script to print out a list of installed packages). If you need additional packages, you can use R’s built-in package manager to install and load them: simply USE THE DOMINO COMMAND LINE INTERFACE (CLI) Use the Domino command line interface (CLI) ¶. Use the Domino command line interface (CLI) ¶. Installing the Domino Command Line (CLI) CLI reference. Downloading files with the CLI. Force restoring a local project. How to move a project from one Domino deployment to another. Using the CLI behind a GIT REPOSITORIES IN DOMINO Overview ¶. Domino supports adding Git repositories to projects. Repositories that have been added to a project are available to Runs started in that project, allowing you to access the contents of those repositories just as you would your Domino files. DOWNLOADING INDIVIDUAL FILES OR FOLDERS WITH THE CLI Downloading individual files or folders with the CLI. If you need to download individual files from a project, the simplest way to do this is from the Files page in the UI. However, if your files are too numerous to manage from the UI, there is an alternate method using a CLI command: domino download-results. This command accepts a filterthat
GETTING STARTED WITH FLASK Getting started with Flask¶. The following guide will set up your Domino project more as a proper web site powered by Flask. This isn’t difficult; you just need to make sure all the folders and files are in place to ensure the app runs correctly. BIOINFORMATICS AND THE UNPRECEDENTED COVID-19 VACCINE RACE Fiona Hyland, Director of R&D, DNA Sequencing Informatics at Thermo Fisher Scientific, joins host Dave Cole to discuss the field of bioinformatics and its critical role in medical breakthroughs like the COVID-19 vaccine. Listen to Data Science Leaders, a podcast fromDomino Data Lab.
CLOUD DATA SCIENCE
A data science workbench on machines of your choosing. Modern data science techniques depend on powerful CPUs and GPUs. The demand is lumpy, leading to idle resources and wasted costs. Domino lets data scientists spin up large or specialized hardware with one click, pre-configured with the tools they already use (e.g., R, Python,Jupyter).
JUPYTER | DOMINO DATA LAB Do Less DevOps and More Data Science Jupyter is a great tool for data science, and Domino lets you get the most out of it. Domino automatically tracks changes to your notebooks and experiments—code, data, results, and environment—so you can always revert or reproduce old results, and even compare how your notebooks and results havechanged over time.
MODEL PUBLISHING OVERVIEW A Domino model is a REST API endpoint wrapped around a function in your code. The arguments to your function are supplied as parameters in the request payload, and the response from the API includes the return value from your function. When a model is published, Dominofirst
WORKSPACES — DOMINO DOCS 4.4 DOCUMENTATION Overview¶. A Domino workspace is an interactive session where you can conduct research, analyze data, train models, and more. Workspaces enable you to work in a development environment of your choice, like Jupyter notebooks, RStudio, VS Code, and many other customizableenvironments.
HOW CAN I WRITE A CUSTOM SCHEDULE? Custom schedules in Domino are created using the quartz cron scheduler. A full tutorial for the quartz scheduler is located here.As in the screenshot below, you will need to APP PUBLISHING OVERVIEW Overview ¶. When experiments in Domino yield interesting results that you want to share with your colleagues, you can easily do so with a Domino App. Domino Apps host web applications and dashboards with the same elastic infrastructure that powers Jobs and Workspace sessions. Domino supports hosting Apps built with many popular frameworks, including Flask, Shiny, and Dash. SHARING AND COLLABORATION To add collaborators, you must be a Contributor to the project, or the project Owner. Click Settings from the project menu, then click the Access & Sharing tab and scroll down to the Collaborators and permissions panel. You can add new collaborators by their username or email address. If you supply an email address belonging to a Dominouser
GETTING STARTED WITH FLASK Getting started with Flask¶. The following guide will set up your Domino project more as a proper web site powered by Flask. This isn’t difficult; you just need to make sure all the folders and files are in place to ensure the app runs correctly. CONNECTING TO S3 FROM DOMINO Getting a file from an S3-hosted public path ¶. If you have files in S3 that are set to allow public read access, you can fetch those files with Wget from the OS shell of a Domino executor, the same way you would for any other resource on the public Internet. The request for those files will look similar to this: THE ENTERPRISE MLOPS PLATFORM Domino’s enterprise MLOps platform accelerates research, speeds model deployment, and increases collaboration for code-first data science teams at scale. Explore the platform. slide 8 to 12 of 13.CLOUD DATA SCIENCE
A data science workbench on machines of your choosing. Modern data science techniques depend on powerful CPUs and GPUs. The demand is lumpy, leading to idle resources and wasted costs. Domino lets data scientists spin up large or specialized hardware with one click, pre-configured with the tools they already use (e.g., R, Python,Jupyter).
MACHINE LEARNING
Machine learning (ML) is the application of computer algorithms that improve automatically through experience. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmedto do so.
INSTALLING PACKAGES AND DEPENDENCIES R¶. If you’re using Domino for R scripts, you may also want to check out our R Package for controlling Domino in your R IDE.. Most common packages are installed by default (you can include installed.packages() at the start of your script to print out a list of installed packages). If you need additional packages, you can use R’s built-in package manager to install and load them: simply ENVIRONMENT MANAGEMENT Environment management is the practice of creating new Domino environments and editing existing environments to meet your specific language and package needs. This work is typically done by an administrator or advanced Domino user. Here are some examples of whento create or
DOMINO COMMUNITY
Domino Community. Connect with other data scientists and Domino users. Ask questions, get answers, share what you know, learn something new. Sign in to submit feature requests and join discussions in specialized categories. Our community is getting a makeover! We will be migrating to a new community that integrates more closely with our support MODEL PUBLISHING OVERVIEW A Domino model is a REST API endpoint wrapped around a function in your code. The arguments to your function are supplied as parameters in the request payload, and the response from the API includes the return value from your function. When a model is published, Dominofirst
USING VISUAL STUDIO CODE IN DOMINO WORKSPACES Overview ¶. Some Domino Standard Environments support launching Visual Studio Code (VSCode) in interactive Workspaces.VSCode is an open-source multi-language editor maintained by Microsoft. Domino can serve the VSCode application to your browser with the power of code-server from Coder.com.. Prerequisites SHARING AND COLLABORATION To add collaborators, you must be a Contributor to the project, or the project Owner. Click Settings from the project menu, then click the Access & Sharing tab and scroll down to the Collaborators and permissions panel. You can add new collaborators by their username or email address. If you supply an email address belonging to a Dominouser
GIT REPOSITORIES IN DOMINO Overview ¶. Domino supports adding Git repositories to projects. Repositories that have been added to a project are available to Runs started in that project, allowing you to access the contents of those repositories just as you would your Domino files. THE ENTERPRISE MLOPS PLATFORM Domino’s enterprise MLOps platform accelerates research, speeds model deployment, and increases collaboration for code-first data science teams at scale. Explore the platform. slide 8 to 12 of 13.CLOUD DATA SCIENCE
A data science workbench on machines of your choosing. Modern data science techniques depend on powerful CPUs and GPUs. The demand is lumpy, leading to idle resources and wasted costs. Domino lets data scientists spin up large or specialized hardware with one click, pre-configured with the tools they already use (e.g., R, Python,Jupyter).
MACHINE LEARNING
Machine learning (ML) is the application of computer algorithms that improve automatically through experience. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmedto do so.
INSTALLING PACKAGES AND DEPENDENCIES R¶. If you’re using Domino for R scripts, you may also want to check out our R Package for controlling Domino in your R IDE.. Most common packages are installed by default (you can include installed.packages() at the start of your script to print out a list of installed packages). If you need additional packages, you can use R’s built-in package manager to install and load them: simply ENVIRONMENT MANAGEMENT Environment management is the practice of creating new Domino environments and editing existing environments to meet your specific language and package needs. This work is typically done by an administrator or advanced Domino user. Here are some examples of whento create or
DOMINO COMMUNITY
Domino Community. Connect with other data scientists and Domino users. Ask questions, get answers, share what you know, learn something new. Sign in to submit feature requests and join discussions in specialized categories. Our community is getting a makeover! We will be migrating to a new community that integrates more closely with our support MODEL PUBLISHING OVERVIEW A Domino model is a REST API endpoint wrapped around a function in your code. The arguments to your function are supplied as parameters in the request payload, and the response from the API includes the return value from your function. When a model is published, Dominofirst
USING VISUAL STUDIO CODE IN DOMINO WORKSPACES Overview ¶. Some Domino Standard Environments support launching Visual Studio Code (VSCode) in interactive Workspaces.VSCode is an open-source multi-language editor maintained by Microsoft. Domino can serve the VSCode application to your browser with the power of code-server from Coder.com.. Prerequisites SHARING AND COLLABORATION To add collaborators, you must be a Contributor to the project, or the project Owner. Click Settings from the project menu, then click the Access & Sharing tab and scroll down to the Collaborators and permissions panel. You can add new collaborators by their username or email address. If you supply an email address belonging to a Dominouser
GIT REPOSITORIES IN DOMINO Overview ¶. Domino supports adding Git repositories to projects. Repositories that have been added to a project are available to Runs started in that project, allowing you to access the contents of those repositories just as you would your Domino files. DATA SCIENCE PRODUCT FOR THE FULL LIFECYCLE Domino is the enterprise data science management platform - where data science work gets done across Data Scientists, IT, and Technical Leaders. Data Science is hard, given constantly changing technologies, burdensome infrastructure requirements across IT, and governance needs ABOUT US | DOMINO DATA LAB About Us. Domino is the Enterprise MLOps platform trusted by over 20% of the Fortune 100. Our products enable thousands of data scientists to develop better medicines, grow more productive crops, adapt risk models to major economic shifts, build better cars, improve customer support, or simply recommend the best purchase to make at the righttime.
DATA SCIENCE WORKBENCH Accelerate Collaborative Research and Development. Domino’s data science workbench provides the flexibility and power that data scientists need to accelerate research and make breakthroughs that deliver real business impact. They can use the tools they want, on hardware optimized for the task at hand, in a governed and scalableenvironment
MODEL RISK MANAGEMENT Model Risk Management. Innovation in data science and modeling has outpaced existing risk management systems. The set of tools, complexity of models, and number of stakeholders are all increasing—and results are used across more parts of the business. The potential is huge, but the downside could be devastating. DATA SCIENCE BLOG BY DOMINO The importance of structure, coding style, and refactoring in notebooks. Notebooks are increasingly crucial in the data scientist's toolbox. Although considered relatively new, their history traces back to systems like Mathematica and MATLAB. Best Practices. Data Science.INSTALLATION
Private or offline installation. Downloading. Extracting and loading. Installing. Configuration. fleetcommand-agent release notes. fleetcommand-agent v37 (March 2021) fleetcommand-agent v34 (February 2021) fleetcommand-agent v33 (February 2021) REV 3 | ENTERPRISE MLOPS LEADERSHIP SUMMIT | DOMINO DATA LAB Rev is the marquee conference for data science and MLOps leaders. At Rev 3, we'll have notable public figures from business and entertainment, executive data science leaders, and industry experts present on the most important topics related to accelerating the development and deployment of data science in the enterprise. You’lllearn critical
USING VISUAL STUDIO CODE IN DOMINO WORKSPACES Overview ¶. Some Domino Standard Environments support launching Visual Studio Code (VSCode) in interactive Workspaces.VSCode is an open-source multi-language editor maintained by Microsoft. Domino can serve the VSCode application to your browser with the power of code-server from Coder.com.. Prerequisites SHARING AND COLLABORATION To add collaborators, you must be a Contributor to the project, or the project Owner. Click Settings from the project menu, then click the Access & Sharing tab and scroll down to the Collaborators and permissions panel. You can add new collaborators by their username or email address. If you supply an email address belonging to a Dominouser
USER MANAGEMENT
User management ¶. User management. ¶. Admin roles. About the Project Manager Role. License usage reporting. Overview. Tracking user license types. Generating user activity reports. THE ENTERPRISE MLOPS PLATFORM Domino’s enterprise MLOps platform accelerates research, speeds model deployment, and increases collaboration for code-first data science teams at scale. Explore the platform. slide 8 to 12 of 13.MACHINE LEARNING
Machine learning (ML) is the application of computer algorithms that improve automatically through experience. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmedto do so.
JUPYTER | DOMINO DATA LAB Do Less DevOps and More Data Science Jupyter is a great tool for data science, and Domino lets you get the most out of it. Domino automatically tracks changes to your notebooks and experiments—code, data, results, and environment—so you can always revert or reproduce old results, and even compare how your notebooks and results havechanged over time.
INSTALLING PACKAGES AND DEPENDENCIES R¶. If you’re using Domino for R scripts, you may also want to check out our R Package for controlling Domino in your R IDE.. Most common packages are installed by default (you can include installed.packages() at the start of your script to print out a list of installed packages). If you need additional packages, you can use R’s built-in package manager to install and load them: simply ENVIRONMENT MANAGEMENT Environment management is the practice of creating new Domino environments and editing existing environments to meet your specific language and package needs. This work is typically done by an administrator or advanced Domino user. Here are some examples of whento create or
SHARING AND COLLABORATION To add collaborators, you must be a Contributor to the project, or the project Owner. Click Settings from the project menu, then click the Access & Sharing tab and scroll down to the Collaborators and permissions panel. You can add new collaborators by their username or email address. If you supply an email address belonging to a Dominouser
USING VISUAL STUDIO CODE IN DOMINO WORKSPACES Overview ¶. Some Domino Standard Environments support launching Visual Studio Code (VSCode) in interactive Workspaces.VSCode is an open-source multi-language editor maintained by Microsoft. Domino can serve the VSCode application to your browser with the power of code-server from Coder.com.. Prerequisites GIT REPOSITORIES IN DOMINO Overview ¶. Domino supports adding Git repositories to projects. Repositories that have been added to a project are available to Runs started in that project, allowing you to access the contents of those repositories just as you would your Domino files. HOW TO TROUBLESHOOT AUTOSCALING(ASG) ISSUES Edit deployment to resolve any differences. kubectl get configmap cluster-autoscaler-status -n -o yaml. kubectl edit deployment -n . Check that each ASG has only 1 Availability Zone. This should be checked both in AWS console, and in the configmap command shown above. GETTING STARTED WITH FLASK Getting started with Flask¶. The following guide will set up your Domino project more as a proper web site powered by Flask. This isn’t difficult; you just need to make sure all the folders and files are in place to ensure the app runs correctly. THE ENTERPRISE MLOPS PLATFORM Domino’s enterprise MLOps platform accelerates research, speeds model deployment, and increases collaboration for code-first data science teams at scale. Explore the platform. slide 8 to 12 of 13.MACHINE LEARNING
Machine learning (ML) is the application of computer algorithms that improve automatically through experience. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmedto do so.
JUPYTER | DOMINO DATA LAB Do Less DevOps and More Data Science Jupyter is a great tool for data science, and Domino lets you get the most out of it. Domino automatically tracks changes to your notebooks and experiments—code, data, results, and environment—so you can always revert or reproduce old results, and even compare how your notebooks and results havechanged over time.
INSTALLING PACKAGES AND DEPENDENCIES R¶. If you’re using Domino for R scripts, you may also want to check out our R Package for controlling Domino in your R IDE.. Most common packages are installed by default (you can include installed.packages() at the start of your script to print out a list of installed packages). If you need additional packages, you can use R’s built-in package manager to install and load them: simply ENVIRONMENT MANAGEMENT Environment management is the practice of creating new Domino environments and editing existing environments to meet your specific language and package needs. This work is typically done by an administrator or advanced Domino user. Here are some examples of whento create or
SHARING AND COLLABORATION To add collaborators, you must be a Contributor to the project, or the project Owner. Click Settings from the project menu, then click the Access & Sharing tab and scroll down to the Collaborators and permissions panel. You can add new collaborators by their username or email address. If you supply an email address belonging to a Dominouser
USING VISUAL STUDIO CODE IN DOMINO WORKSPACES Overview ¶. Some Domino Standard Environments support launching Visual Studio Code (VSCode) in interactive Workspaces.VSCode is an open-source multi-language editor maintained by Microsoft. Domino can serve the VSCode application to your browser with the power of code-server from Coder.com.. Prerequisites GIT REPOSITORIES IN DOMINO Overview ¶. Domino supports adding Git repositories to projects. Repositories that have been added to a project are available to Runs started in that project, allowing you to access the contents of those repositories just as you would your Domino files. HOW TO TROUBLESHOOT AUTOSCALING(ASG) ISSUES Edit deployment to resolve any differences. kubectl get configmap cluster-autoscaler-status -n -o yaml. kubectl edit deployment -n . Check that each ASG has only 1 Availability Zone. This should be checked both in AWS console, and in the configmap command shown above. GETTING STARTED WITH FLASK Getting started with Flask¶. The following guide will set up your Domino project more as a proper web site powered by Flask. This isn’t difficult; you just need to make sure all the folders and files are in place to ensure the app runs correctly.CLOUD DATA SCIENCE
A data science workbench on machines of your choosing. Modern data science techniques depend on powerful CPUs and GPUs. The demand is lumpy, leading to idle resources and wasted costs. Domino lets data scientists spin up large or specialized hardware with one click, pre-configured with the tools they already use (e.g., R, Python,Jupyter).
DOMINO DATA SCIENCE PLATFORM Domino centralizes data science work and infrastructure across the enterprise for collaboratively building, training, deploying, and managing models – faster and more efficiently. With Domino, data scientists can innovate faster, teams reuse work and collaborate more, and IT teams can manage and govern infrastructure. Start Trial. MANAGING DATA SCIENCE TEAMS How to improve knowledge management. There are four steps that can help data science leaders improve knowledge management in their enterprise organizations: 1. Capture as much knowledge as possible in one place. The more things are in there, the more connections you have across them, and the value grows that way.DOMINO COMMUNITY
Domino Community. Connect with other data scientists and Domino users. Ask questions, get answers, share what you know, learn something new. Sign in to submit feature requests and join discussions in specialized categories. Our community is getting a makeover! We will be migrating to a new community that integrates more closely with our support MODEL PUBLISHING OVERVIEW A Domino model is a REST API endpoint wrapped around a function in your code. The arguments to your function are supplied as parameters in the request payload, and the response from the API includes the return value from your function. When a model is published, Dominofirst
WORKSPACES — DOMINO DOCS 4.4 DOCUMENTATION Overview¶. A Domino workspace is an interactive session where you can conduct research, analyze data, train models, and more. Workspaces enable you to work in a development environment of your choice, like Jupyter notebooks, RStudio, VS Code, and many other customizableenvironments.
GETTING STARTED WITH FLASK Getting started with Flask¶. The following guide will set up your Domino project more as a proper web site powered by Flask. This isn’t difficult; you just need to make sure all the folders and files are in place to ensure the app runs correctly. HOW TO TROUBLESHOOT AUTOSCALING(ASG) ISSUES Edit deployment to resolve any differences. kubectl get configmap cluster-autoscaler-status -n -o yaml. kubectl edit deployment -n . Check that each ASG has only 1 Availability Zone. This should be checked both in AWS console, and in the configmap command shown above. HOW MUCH DOES DOMINO COST? How much does Domino cost? Domino Data Lab is priced as an annual subscription that depends on where Domino is running (our hosted infrastructure, your private cloud, or on premise). When running in our hosted environment, we also charge usage fees for the compute time you use. To learn more about pricing, contact us or request a demotoday.
INCREASING THE TIMEOUT FOR SHINY SERVER Increasing the timeout for Shiny Server. When accessing your published Shiny Server, the app will timeout after the default setting of 60 seconds of inactivity. If you need to increase this timeout then there are two ways to increase the timeout: 1) If your team has a Shiny Server Pro license then you could set this up within your Domino THE ENTERPRISE MLOPS PLATFORM Domino’s enterprise MLOps platform accelerates research, speeds model deployment, and increases collaboration for code-first data science teams at scale. Explore the platform. slide 8 to 12 of 13.CLOUD DATA SCIENCE
A data science workbench on machines of your choosing. Modern data science techniques depend on powerful CPUs and GPUs. The demand is lumpy, leading to idle resources and wasted costs. Domino lets data scientists spin up large or specialized hardware with one click, pre-configured with the tools they already use (e.g., R, Python,Jupyter).
MACHINE LEARNING
Machine learning (ML) is the application of computer algorithms that improve automatically through experience. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmedto do so.
INSTALLING PACKAGES AND DEPENDENCIES R¶. If you’re using Domino for R scripts, you may also want to check out our R Package for controlling Domino in your R IDE.. Most common packages are installed by default (you can include installed.packages() at the start of your script to print out a list of installed packages). If you need additional packages, you can use R’s built-in package manager to install and load them: simply ENVIRONMENT MANAGEMENT Environment management is the practice of creating new Domino environments and editing existing environments to meet your specific language and package needs. This work is typically done by an administrator or advanced Domino user. Here are some examples of whento create or
DOMINO COMMUNITY
Domino Community. Connect with other data scientists and Domino users. Ask questions, get answers, share what you know, learn something new. Sign in to submit feature requests and join discussions in specialized categories. Our community is getting a makeover! We will be migrating to a new community that integrates more closely with our support MODEL PUBLISHING OVERVIEW A Domino model is a REST API endpoint wrapped around a function in your code. The arguments to your function are supplied as parameters in the request payload, and the response from the API includes the return value from your function. When a model is published, Dominofirst
USING VISUAL STUDIO CODE IN DOMINO WORKSPACES Overview ¶. Some Domino Standard Environments support launching Visual Studio Code (VSCode) in interactive Workspaces.VSCode is an open-source multi-language editor maintained by Microsoft. Domino can serve the VSCode application to your browser with the power of code-server from Coder.com.. Prerequisites SHARING AND COLLABORATION To add collaborators, you must be a Contributor to the project, or the project Owner. Click Settings from the project menu, then click the Access & Sharing tab and scroll down to the Collaborators and permissions panel. You can add new collaborators by their username or email address. If you supply an email address belonging to a Dominouser
GIT REPOSITORIES IN DOMINO Overview ¶. Domino supports adding Git repositories to projects. Repositories that have been added to a project are available to Runs started in that project, allowing you to access the contents of those repositories just as you would your Domino files. THE ENTERPRISE MLOPS PLATFORM Domino’s enterprise MLOps platform accelerates research, speeds model deployment, and increases collaboration for code-first data science teams at scale. Explore the platform. slide 8 to 12 of 13.CLOUD DATA SCIENCE
A data science workbench on machines of your choosing. Modern data science techniques depend on powerful CPUs and GPUs. The demand is lumpy, leading to idle resources and wasted costs. Domino lets data scientists spin up large or specialized hardware with one click, pre-configured with the tools they already use (e.g., R, Python,Jupyter).
MACHINE LEARNING
Machine learning (ML) is the application of computer algorithms that improve automatically through experience. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmedto do so.
INSTALLING PACKAGES AND DEPENDENCIES R¶. If you’re using Domino for R scripts, you may also want to check out our R Package for controlling Domino in your R IDE.. Most common packages are installed by default (you can include installed.packages() at the start of your script to print out a list of installed packages). If you need additional packages, you can use R’s built-in package manager to install and load them: simply ENVIRONMENT MANAGEMENT Environment management is the practice of creating new Domino environments and editing existing environments to meet your specific language and package needs. This work is typically done by an administrator or advanced Domino user. Here are some examples of whento create or
DOMINO COMMUNITY
Domino Community. Connect with other data scientists and Domino users. Ask questions, get answers, share what you know, learn something new. Sign in to submit feature requests and join discussions in specialized categories. Our community is getting a makeover! We will be migrating to a new community that integrates more closely with our support MODEL PUBLISHING OVERVIEW A Domino model is a REST API endpoint wrapped around a function in your code. The arguments to your function are supplied as parameters in the request payload, and the response from the API includes the return value from your function. When a model is published, Dominofirst
USING VISUAL STUDIO CODE IN DOMINO WORKSPACES Overview ¶. Some Domino Standard Environments support launching Visual Studio Code (VSCode) in interactive Workspaces.VSCode is an open-source multi-language editor maintained by Microsoft. Domino can serve the VSCode application to your browser with the power of code-server from Coder.com.. Prerequisites SHARING AND COLLABORATION To add collaborators, you must be a Contributor to the project, or the project Owner. Click Settings from the project menu, then click the Access & Sharing tab and scroll down to the Collaborators and permissions panel. You can add new collaborators by their username or email address. If you supply an email address belonging to a Dominouser
GIT REPOSITORIES IN DOMINO Overview ¶. Domino supports adding Git repositories to projects. Repositories that have been added to a project are available to Runs started in that project, allowing you to access the contents of those repositories just as you would your Domino files. DATA SCIENCE PRODUCT FOR THE FULL LIFECYCLE Domino is the enterprise data science management platform - where data science work gets done across Data Scientists, IT, and Technical Leaders. Data Science is hard, given constantly changing technologies, burdensome infrastructure requirements across IT, and governance needs ABOUT US | DOMINO DATA LAB About Us. Domino is the Enterprise MLOps platform trusted by over 20% of the Fortune 100. Our products enable thousands of data scientists to develop better medicines, grow more productive crops, adapt risk models to major economic shifts, build better cars, improve customer support, or simply recommend the best purchase to make at the righttime.
DATA SCIENCE WORKBENCH Accelerate Collaborative Research and Development. Domino’s data science workbench provides the flexibility and power that data scientists need to accelerate research and make breakthroughs that deliver real business impact. They can use the tools they want, on hardware optimized for the task at hand, in a governed and scalableenvironment
MODEL RISK MANAGEMENT Model Risk Management. Innovation in data science and modeling has outpaced existing risk management systems. The set of tools, complexity of models, and number of stakeholders are all increasing—and results are used across more parts of the business. The potential is huge, but the downside could be devastating. DATA SCIENCE BLOG BY DOMINO The importance of structure, coding style, and refactoring in notebooks. Notebooks are increasingly crucial in the data scientist's toolbox. Although considered relatively new, their history traces back to systems like Mathematica and MATLAB. Best Practices. Data Science.INSTALLATION
Private or offline installation. Downloading. Extracting and loading. Installing. Configuration. fleetcommand-agent release notes. fleetcommand-agent v37 (March 2021) fleetcommand-agent v34 (February 2021) fleetcommand-agent v33 (February 2021) REV 3 | ENTERPRISE MLOPS LEADERSHIP SUMMIT | DOMINO DATA LAB Rev is the marquee conference for data science and MLOps leaders. At Rev 3, we'll have notable public figures from business and entertainment, executive data science leaders, and industry experts present on the most important topics related to accelerating the development and deployment of data science in the enterprise. You’lllearn critical
USING VISUAL STUDIO CODE IN DOMINO WORKSPACES Overview ¶. Some Domino Standard Environments support launching Visual Studio Code (VSCode) in interactive Workspaces.VSCode is an open-source multi-language editor maintained by Microsoft. Domino can serve the VSCode application to your browser with the power of code-server from Coder.com.. Prerequisites SHARING AND COLLABORATION To add collaborators, you must be a Contributor to the project, or the project Owner. Click Settings from the project menu, then click the Access & Sharing tab and scroll down to the Collaborators and permissions panel. You can add new collaborators by their username or email address. If you supply an email address belonging to a Dominouser
USER MANAGEMENT
User management ¶. User management. ¶. Admin roles. About the Project Manager Role. License usage reporting. Overview. Tracking user license types. Generating user activity reports.*
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