Jump to content

Search the Community

Showing results for tags 'release notes'.

  • Search By Tags

    Type tags separated by commas.
  • Search By Author

Content Type


Forums

  • Lucd AI Platform Suite
    • JedAI Client
    • Python Client
    • Modeling Framework
    • General
  • Collaborate & Discuss
    • Questions & Answers
    • Data Management
    • Machine Learning
    • AI Solutions
    • Community Feedback & Requests
  • Health & Life Sciences's Discussion
  • Financial Services's Discussion
  • Retail & Consumer Packaged Goods's Discussion
  • Media & Entertainment's Discussion
  • Energy's Discussion
  • Manufacturing's Topics

Blogs

  • Lucd Team Blog
  • UX Club (Beta version only)'s Blog

Calendars

  • Community Calendar
  • Health & Life Sciences's Events
  • Financial Services's Events
  • Retail & Consumer Packaged Goods's Events
  • Media & Entertainment's Events
  • Energy's Events
  • Manufacturing's Events

Categories

  • Datasheets and White Papers
  • Press Releases
  • Industry Focus
    • Energy
    • Financial Services
    • Health and Life Services
    • Media and Entertainment
    • Manufacturing
    • Retail

Categories

  • JedAI Client
  • Python Client
  • Modeling Framework
  • General

Find results in...

Find results that contain...


Date Created

  • Start

    End


Last Updated

  • Start

    End


Filter by number of...

Joined

  • Start

    End


Group


About Me


Interests


Industry

Found 6 results

  1. Enables the ability to authenticate to Lucd backend and access data for custom analysis and model prototyping. Enables the ability to define custom feature transformation operations, and upload to Lucd for use in the GUI. Provides access to the Asset, Concept, Custom Contract, Custom Operation, Explore, Model, UDS and VDS REST APIs. Provides multiple working examples of individual REST calls, as well as complete models. Enables Dask exploration of the data on the client side. Enables development and testing of model development using the Lucd PyTorch, Tensorflow, Keras and XGBoost classes. View full record
  2. New Features Added the “compact modeling” framework, enabling end-users to avoid writing boilerplate code (e.g., data retrieval, performance analysis) when preparing models. This now supports PyTorch and TensorFlow. Added capability for producing customizable real-time training update graphs for TensorFlow and PyTorch modeling. Other graphs (e.g., precision-recall) have been added as well. Added interactive confusion matrix capabilities, enabling detailed view of mis-labeled testing data, etc. Added capability to evaluate output of trained models in the JedAI Unity client via the explainability tab. Works for TensorFlow and PyTorch tabular, image and text classification as well as regression models. Changes Expanded use of “model_type” parameter to include “tabular_classification,” alleviating need to perform guesswork in code to determine model type. Refactored/improved retrieval code for virtual datasets and predictions to consider differences between TensorFlow and PyTorch data. TensorFlow models must now return all four of ordered_class_names, ordered_feature_names, input_name and output_name with compact modeling. PyTorch models must return ordered_class_names with compact modeling. Code refactoring to fix input and output mappings with TensorFlow models Various other bugfixes Miscellaneous code refactoring to make PyTorch modeling less error-prone. Enablement of ElasticSearch upgrades, minor related bugfixes
  3. New Features Added the “compact modeling” framework, enabling end-users to avoid writing boilerplate code (e.g., data retrieval, performance analysis) when preparing models. This now supports PyTorch and TensorFlow. Added capability for producing customizable real-time training update graphs for TensorFlow and PyTorch modeling. Other graphs (e.g., precision-recall) have been added as well. Added interactive confusion matrix capabilities, enabling detailed view of mis-labeled testing data, etc. Added capability to evaluate output of trained models in the JedAI Unity client via the explainability tab. Works for TensorFlow and PyTorch tabular, image and text classification as well as regression models. Changes Expanded use of “model_type” parameter to include “tabular_classification,” alleviating need to perform guesswork in code to determine model type. Refactored/improved retrieval code for virtual datasets and predictions to consider differences between TensorFlow and PyTorch data. TensorFlow models must now return all four of ordered_class_names, ordered_feature_names, input_name and output_name with compact modeling. PyTorch models must return ordered_class_names with compact modeling. Code refactoring to fix input and output mappings with TensorFlow models Various other bugfixes Miscellaneous code refactoring to make PyTorch modeling less error-prone. Enablement of ElasticSearch upgrades, minor related bugfixes View full record
  4. Enables the ability to authenticate to Lucd backend and access data for custom analysis and model prototyping. Enables the ability to define custom feature transformation operations, and upload to Lucd for use in the GUI. Provides access to the Asset, Concept, Custom Contract, Custom Operation, Explore, Model, UDS and VDS REST APIs. Provides multiple working examples of individual REST calls, as well as complete models. Enables Dask exploration of the data on the client side. Enables development and testing of model development using the Lucd PyTorch, Tensorflow, Keras and XGBoost classes.
  5. New Features This release contains improvements to model profile features. Additional tooltips Model Profile improvements, including: Tabular Data Predict allows multiple JSON records of input to be predicted and output Tabular/Regression Explain provides further explanation of a tabular data prediction Image Explain allows users to upload images and generate explanations of predictions Text Explain allows users to send text input and receive an explanation of predictions
  6. New Features This release contains improvements to model profile features. Additional tooltips Model Profile improvements, including: Tabular Data Predict allows multiple JSON records of input to be predicted and output Tabular/Regression Explain provides further explanation of a tabular data prediction Image Explain allows users to upload images and generate explanations of predictions Text Explain allows users to send text input and receive an explanation of predictions View full record

HELP & SUPPORT

ABOUT US

Lucd is an AI software platform company that supports multiple industry verticals, allowing for its users to build enterprise-ready AI solutions with Low Code / No Code development practices. Lucd supports the entire AI lifecycle, allowing for the secure fusing of structured and unstructured data, empowering data analysts as well as business professionals to work collaboratively, resulting in reduced time to uncover new opportunities and solutions.

×
×
  • Create New...