Data Processing, Tokenization, & Sentiment Analysis

AI Practitioner

• Overview
• Sentiment Analysis Overview
  
  • What is Sentiment Analysis?
  • Why use Deep Learning for Sentiment Analysis?
  • Dataset
  • Objective
  • Preprocessing with RAPIDS
  • Tokenization
  • Why do we need RAPIDS for Tokenization
• Step #1: Training the Sentiment Analysis Model
  
  • Lab Basics
  • Train the Model
• Triton Inference Server Overview
  
  • Deploy the Trained model on the Triton Inference server
    
    • Triton Inference Server
    • Model Repository
    • Why use the RAPIDS tokenizer inside Triton Inference Server?
    • RAPIDS and PyTorch Ensemble Inside Triton Inference Server
    • Sentiment Analysis Model Repository Format
  • RAPIDS Tokenizer Model
    
    • CONFIG.PBTXT
    • MODEL.PY
  • Sentiment Analysis Model
    
    • CONFIG.PBTXT
    • MODEL.PY
  • End-to-end Model
    
    • CONFIG.PBTXT
• Step #2: Start the Triton Inference Server
• Step #3: Client Application
• Next Steps

Notices

• Legal
  
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