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The Beginner’s Guide to Building Custom Language AI Models

About This Workshop

Youtube Video

About This Workshop
Enterprise textual data has significant value related to core business activities and their customers. To gain business and customer insights effectively and at scale from this text data, natural language processing capabilities are needed. For example, identifying key requirements in RFPs to respond effectively or understand customer perception of their products to address gaps. Some core language processing capabilities include detecting languages, translating content, extracting key elements, classifying intent and detecting the sentiment expressed in the text. These capabilities are typically machine learning algorithms custom built, tuned by Data Scientists and productized for use in applications. Doing this is a time consuming and expensive proposition.

OCI Language service reduces this time and effort, by providing key language processing capabilities via production ready REST APIs. The service enables applications to automate sophisticated text analysis at scale without needing ML expertise. The service functionality is implemented with pre-trained ML models which are often useful. They may also be further customized to understand the language patterns of the customer’s context by providing additional data.These capabilities are expected of and provided by all hyperscale public clouds.

Workshop Info

1 hour, 30 minutes
  • Introduction: OCI Language
  • Working with Pre-Trained NLP Models
    • Analyzing Text with the Console
    • Access OCI Language with OCI Console
    • Access OCI Language with Language SDKs
    • Access OCI Language with Rest API
    • Access OCI Language in DataScience Notebook Session.
  • Working with Custom Models
    • Creating projects
    • Creating and training Custom NER model using OCI console
    • Creating and training Custom Text Classification model OCI Console
    • Creating and training custom models using Python SDK
  • Using Text Translation Service
    • Translating text using OCI Console
    • Translating text using Python SDK


  • Familiar with OCI Policy and SDK/CLI setup.
  • Familiar with Python/Java programming for SDK usage is strongly recommended.
  • Familiar with OCI  services DataScience is recommended, but not required.

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