Data Science
106 Release Notes
AI Quick Actions v 1.0.4 are now Available in Data Science
- perplexity score
- text ...
AI Quick Actions v 1.0.3 are now Available in Data Science
- Arm compute shapes
- The llama.cpp container
- Importing ...
Data Science now Supports Large Models
Data Science Model Deployment and Model Catalog services now support large model deployments.
Large model artifacts can be stored ...
Use your own Models with Data Science AI Quick Actions
If you have models you want to use instead of those curated by Data Science, you can bring them into ...
Data Science now Supports Deeplinking inside Data Science Notebook.
Deeplinking into a Notebook Session enables customers of OCI Data Science to open a notebook session at a file path ...
Data Science now offers ML Monitoring
Data Science ML Monitoring lets you:
- Read data from Object Storage using the built-in data readers.
- Extend ...
AI Quick Actions are now Available in Data Science
AI quick actions makes it easy for you to browse a curated list of foundation models, and deploy, fine-tune, and ...
Burstable Instances for Model Deployment in Data Science is now Available
Key Features
- Burstable Instances for Machine Learning: Lets deployment of machine learning models on virtual machines with ...
Autoscaling for Model Deployments in Data Science is now Available
Some Key benefits of autoscaling for model deployment include:
-
Dynamic Resource Adjustment: Autoscaling automatically increases or decreases ...
New Data Science Conda Environments are Introduced
The following conda environments are introduced:
Data Science: Notebook JupyterLab Version is now 3.6.6
Data Science notebooks now use JupyterLab version 3.6.6.
Data Science: Bring Your Own Containers with Improved Functionality
- You can now manage your containers more efficiently with our new ML Jobs APIs and Console.
- Upload and ...
Accelerated Data Science 2.10.1 is Released
The following changes were made in ADS 2.10.1:
-
Releasing v1 of the Anomaly Detection Operator! The Anomaly ...
New Data Science Conda Environments are Introduced
The following conda environments are introduced:
Accelerated Data Science 2.10.0 is released
The following changes were made in ADS 2.10.0:
- Improved the progress bar to use the percentage completed of ...
Accelerated Data Science 2.9.1 is released
The following changes were made in ADS 2.9.1:
- Added support for deploying LangChain application as OCI Model Deployment. ...
Accelerated Data Science 2.9.0 is Released
The following changes were made in ADS 2.9.0:
- Introducing AI Forecast Operator. Learn more about Operators in the ...
Accelerated Data Science 2.8.11 is released
The following changes were made in ADS 2.8.11:
- Added support to mount file systems in Data Science notebook ...
Storage mounts are introduced.
You can now specify File Storage service mount points or Object Storage service buckets in notebook sessions and jobs. This ...
Notebook session lifecycle scripts
You can now use the notebook session lifecycle scripts to run a custom script at different notebook session lifecycle states ...
Private endpoint to access notebook sessions
You can now configure a private endpoint in your tenancy. Use a private endpoint to access one or more notebook ...
Accelerated Data Science 2.8.10 is released
The following changes were made in ADS 2.8.10:
- Improved the
LargeArtifactUploader
class to understand OCI paths to upload ...
Accelerated Data Science 2.8.9 is released
The following changes were made in ADS 2.8.9:
- Upgraded the
scikit-learn
dependency to >=1.0. - Upgraded the
pandas ...
Accelerated Data Science 2.8.8 is released
The following changes were made in ADS 2.8.8:
- Added
PyTorchDistributed
runtime option for Data Science jobs to add ...
Accelerated Data Science 2.8.7 is released
The following changes were made in ADS 2.8.7:
- Removed incorrect help information of
opctl
commands. - Add pre-commit ...
Accelerated Data Science 2.8.6 is released
The following changes were made in ADS 2.8.6:
- Resolved an issue in
ads opctl build-image job-local
when the ...
Accelerated Data Science 2.8.5 is released
The following changes were made in ADS 2.8.5:
- Added support for
key_content
attribute inads.set_auth()
for the API ...
Accelerated Data Science 2.8.4 is released
The following changes were made in ADS 2.8.4:
- Added support for creating
ADSDataset
from pandas dataframe. - Added ...
Accelerated Data Science 2.8.3 is released
The following changes were made in ADS 2.8.3:
-
Added support for custom containers (Bring Your Own Container ...
Accelerated Data Science 2.8.2 is released
The following changes were made in ADS 2.8.2:
-
Removed support for Python 3.7.
-
Improved ...
Data Science notebook session JupyterLab interface enhancements
- The Launcher has been updated with an icon caching mechanism and a Getting Started notebook as a separate button ...
Accelerated Data Science 2.8.1 is released
The following changes were made in ADS 2.8.1:
-
Fixed a bug for
ads opctl run
when--auth ...
Accelerated Data Science 2.8.0 is released
The following changes were made in ADS 2.8.0:
-
Added support for the machine learning pipelines feature.
...
Pipelines and pipeline runs are introduced.
Machine learning pipelines are a crucial component of the modern data science workflow. They help automate the process of building, ...
Accelerated Data Science 2.7.3 is released
The following changes were made in ADS 2.7.3:
-
Added support for the model version set feature.
...
Introducing Model Versioning in Model Catalogs
Model versioning enables you to keep records of the different models that you've trained, and your various attempts at improving ...
Data Science notebook session timeout change
We have simplified the process so that there is only one option to extend a notebook session to the maximum ...
Data Science is Available in US Midwest (Chicago)
Data Science is now available in the US Midwest (Chicago) region.
For more information about Data Science and features ...
Accelerated Data Science 2.7.0 is released
The following changes were made in ADS 2.7.0:
-
Fixed a bug in
GenericModel.prepare
. The.model-ignore
file ...
Data Science now connects to Data Flow
You can connect to Data Flow and run an Apache Spark application from a Data Science notebook session. These sessions ...
Accelerated Data Science 2.6.8 and 2.6.9 are released
The following changes were made in ADS 2.6.8 and ADS 2.6.7.
2.6.8
- Fixed a bug in
ads.dataset.helper ...
Accelerated Data Science 2.6.4 is released
Accelerated Data Science added support for large models that are models with artifacts between 2 and 6 GB. An Object ...
Introducing Flexible Compute Shapes for Notebook Sessions and Jobs
- Data Science notebook sessions now support new flexible compute shapes.
- Data Science jobs now support flexible compute shapes. ...
Accelerated Data Science 2.6.3 is released
The following changes were made in this version.
- Added
prepare_save_deploy()
method to theGenericModel
class. Now you can ...
Introducing Runtime Configuration for Notebook Sessions
You can now set up your notebook sessions with your often used custom environment variables and Git repos to be ...
Data Science is Available in Mexico Central (Queretaro)
Data Science is now available in the Mexico Central (Queretaro) region.
For more information about Data Science and features ...
Introducing Flexible Compute Shapes for Model Deployments
You can now use flexible compute shapes for model deployments.
For APIs, see CreateModelDeployment, and ModelDeploymentInstanceShapeConfigDetails. For more ...
Launch of the Notebook Explorer
Example Notebooks
- Release of the new Notebook Explorer extension for JupyterLabs. This extension allows you to search for ...
Accelerated Data Science 2.6.2 is released
The following changes were made in this version.
-
Added
from_model_deployment()
method to theGenericModel
class. Now, you ...
ADS JupyterLab UI Enhancements
The Environment Explorer tab list view has been updated with:
- The Actions menu that allows you to easily ...
Introducing Bring Your Own Container
You can now build and use your own container for use when you create a job and job runs.
...Accelerated Data Science v2.5.10 is released
The following changes were made in this version.
- Added
BDSSecretKeeper
to store and save configuration parameters to connect ...
New conda environments are introduced
The following conda environments are introduced:
Accelerated Data Science v2.5.9 is released
- Added the following framework-specific classes for fast and easy model deployment:
- AutoMLModel
- SKlearnModel
- XGBoostModel
- LightGBMModel ...
Accelerated Data Science v2.5.8 is released
- Fixed bug in automatic extraction of taxonomy metadata for
Sklearn
models. - Fixed bug in jobs
NotebookRuntime
when using ...
Service managed networking resources
You can now choose to let the Data Science service configure your networking resources with public internet access in notebook ...
Financial Services for GPU conda environment is introduced
The Financial Services conda environment is an ecosystem to do portfolio optimization, stock analysis, technical analysis, and other financial econometric ...
PySpark 3.0 and Data Flow conda environment is introduced
With the PySpark 3.0 and Data Flow CPU on Python 3.7 (version 3.0) conda environment you can apply the power ...
Introducing fast launch for jobs
You can use the new fast launch option to automatically select a Compute shape from predefined pool of shapes when ...
Accelerated Data Science v2.5.7 is released
- Fixed bug in DataFlow
Job
creation. - Fixed bug in
ADSDataset get_recommendations
causing anHTML is not defined
exception. ...
Conda environment additions and removals
The following conda environments are introduced:
- The General Machine Learning for CPU and GPU on Python 3.7 conda ...
Data Science now includes job run monitoring
You can now monitor the health, capacity, and performance of Data Science job runs by using metrics, alarms, and notifications. ...
Accelerated Data Science v2.5.6 is released
- Added support for the
storage_options
parameter inADSDataset
.to_hdf()
. - Fixed an error message to specify
overwrite_script
or ...
Enhancements to JupyterLab and new icons
These enhancements were made to the JupyterLab environment:
- The Environment Explorer tab list view has been updated for ...
The JuypterLab Git extension is now included in notebook sessions
The JuypterLab Git extension is now available in notebook sessions. This change came with the latest Notebook Virtual Machine (NBVM) ...
Data Exploration, NVIDIA RAPIDS, and Parallel Graph AnalytiX conda environments
The following conda environments are introduced:
- The Data Exploration and Manipulation for CPU v3 conda environment contains libraries ...
Computer Vision and TensorFlow conda environments are introduced
The Computer Vision for CPU and GPU on Python 3.7 (version 1.0) conda environment include some of the most powerful ...
Data Science now includes model deployment monitoring
You can now monitor the health, capacity, and performance of Data Science model deployments by using metrics, alarms, and notifications. ...
Accelerated Data Science v2.5.5 is released
Fixed a bug in model artifact prepare()
, reload()
, and prepare_generic_model()
resulting in an ``ONNXRuntimeError`` caused by the mismatched ...
Accelerated Data Science v2.5.4 is released
Data Labeling
- Added support to read exported dataset from the consolidated export file.
ADS
-
...
Accelerated Data Science v2.5.3 is released
These features were added in ADS v2.5.3:
ADS
-
Moved
fastavro
,pandavro,
andopenpyxl
to an ...
Introducing notebook session timeout management
You can now extend your notebook session time by up to 23 hours to avoid being logged out after an ...
Neurophysiology, TensorFlow, and PyTorch Conda Environments
The Neurophysiology 1.0 for CPU healthcare focused conda environment provides the best-in-class tooling for analyzing, visualizing and exploring neurophysiological data. ...
Enhancements including ADS v2.5.2 and tutorials
Accelerated Data Science v2.5.2 is released including improved model introspection functionality and the ability to manage credentials with the Vault ...
TensorFlow 2.6 versions 1 and 2 conda environment is introduced.
The TensorFlow conda environment is an ecosystem of tools and libraries to create state-of-the-art machine learning models. You can use ...
Data Science has a new JupyterLab Launcher
We are introducting a new Launcher tab in JupyterLab notebook sessions. When you open the Launcher tab, you'll see that ...
Intel Extension for Scikit-learn 2021.3.0 conda environment is introduced.
Speed up your scikit-learn algorithms with the Intel Extension for Scikit-learn conda environment. It uses the Intel oneAPI Data Analytics ...
Access Object Storage using Pandas
You can now access Object Storage in Pandas. The Data Science service has created the ocifs
library that is based ...
Data Science has updated the Environment Explorer and Spinner extensions.
The Environment Explorer has been extended by adding a new list view. This is an alternative view to the card ...
Accelerated Data Science (ADS) Jobs and Job Runs Feature
The Data Science jobs feature is introduced in ADS v2.4.0 and includes the following:
-
Data Science jobs ...
Jobs and Job Runs are introduced in Data Science
The jobs feature enables you to define and run a repeatable machine learning task on a fully managed infrastructure. Jobs ...
PyTorch 1.9 conda environment is introduced.
Use the new PyTorch 1.9 condas for applications in computer vision and natural language processing. These conda environments are for ...
Accelerated Data Science (ADS) Feature Type and Model Catalog Features
ADS v2.3.1
Model Catalog
This new release of the model catalog is now available. It includes these enhancements: ...
Data Science is Available in the Brazil Southeast (Vinhedo) Region
Data Science is now available in the Brazil Southeast (Vinhedo) region.
For more information about Data Science and features ...
New Release of the Model Catalog in Data Science
This new release of the model catalog is now available. It includes these enhancements:
- New model taxonomy metadata ...
The Jupyter Lab version in notebook sessions is upgraded to version 2.2.6.
The latest version of Jupyter Lab is used when you create a new notebook. You can't choose the older version ...
Parallel Graph AnalytiX (PyPGX) conda environment is introduced.
Use PyPGX V21.3.1 to extract hidden insights using graph machine learning, optimized analytics algorithms, and a graph query language. PyPGX ...
PySpark 2.4 and 3.0 conda environments now support Resource Principal
The Data Science service provides seamless integration with the Data Flow service. You can develop your Spark applications in PySpark ...
PySpark V3.0 conda environment is introduced.
Use the PySpark V3.0 conda to create Data Flow jobs or run PySpark locally. The PySpark version is updated from ...
Data Science now supports the VM.Standard.E3.Flex Compute shape
The VM.Standard.E3.Flex Compute shape is now generally available in the Data Science service in certain regions. For more information, see ...
Data Science is Available in US Government Regions
Data Science is now available in US government regions:
-
US Gov West (Phoenix)
-
US ...
Data Science has updated conda environments plus a new NLP environment
The Data Science service provides conda environments that are specialized for different workflows. In this release, there are six new ...
Data Science has updated the Environment Explorer
Conda environments provide flexibility and reproducibility within the Data Science notebook. The Environment Explorer is GUI tool that allows you ...
Data Science has added a new Model Deployment Feature
Data Science is now available in the Chile (Santiago) region.
Data Science is now available in the Chile (Santiago) region. For more information, see Data Science and Data Science API ...
Data Science is now available in the UK West (Newport) region
Data Science is now available in the UK West (Newport) region. For more information, see Data Science and Data Science ...
Data Science now has conda environments in notebook sessions.
Conda Environments
- Release of the new conda environments feature in notebook sessions. A new Environment Explorer extension is ...
Data Science now includes notebook session monitoring
You can now monitor the health, capacity, and performance of Data Science notebook sessions by using metrics, alarms, and notifications, ...
Data Science now supports GPU Compute shapes
GPUs VMs (P100 and V100) are now generally available within the Oracle Cloud Infrastructure Data Science service in certain regions. ...
Data Science is now available in India South (Hyderabad), South Korea North (Chuncheon), and US West (San Jose) regions
Data Science is now available in India South (Hyderabad), South Korea North (Chuncheon), and US West (San Jose) regions. For ...
Data Science Resource Principals and other Improvements to the Notebook Session Environment are now available
Support for Resource Principals in Notebook Sessions
Oracle Cloud Infrastructure Data Science enables you to authenticate using your notebook ...
Improvements to the Notebook Session Environment and Library Upgrades
Notebook Session Environment
The notebook session environment includes these improvements:
- New Launcher buttons for both the notebook ...
Improvements to the Notebook Session Environment
The Notebook Session environment includes the following changes:
- The
home
folder is now backed by block volume. You ...
Data Science is now available in new regions
Data Science is now available in Australia Southeast (Melbourne), Canada Southeast (Montreal), Japan Central (Osaka), Netherlands Northwest (Amsterdam), and Saudi ...
Data Science JupyterLab environment and the Accelerated Data Science SDK are enhanced
The JupyterLab notebook session interface is enhanced so that the JupyterLab environment now supports:
- The Variable Inspector extension. ...
Data Science is now available
The Data Science service enables data science teams to build, train, and manage machine learning and artificial intelligence models on ...