Embark on a comprehensive 3-hour 38-minute tutorial that guides you through implementing an end-to-end NLP project focused on text summarization, complete with deployment using GitHub Actions. Learn the intricacies of condensing longer texts into concise versions while preserving key information. Follow along as the instructor covers project setup, data ingestion, validation, and transformation, as well as model training, evaluation, and deployment. Gain hands-on experience with creating a prediction pipeline, developing a user app, and implementing CI/CD deployment on AWS. By the end of this in-depth guide, you'll have a thorough understanding of the entire process, from initial setup to final deployment, equipping you with valuable skills in NLP project implementation.
End to End NLP Project Implementation With Deployment Github Action - Text Summarization - Krish Naik
Krish Naik via YouTube
Overview
Syllabus
- Introduction
- Project Introduction
- Prerequisite
- Introduction of the Instructor
- What is Text Summarization Online Demo
- Github Repository Setup
- Project Template Creation
- Requirements Installation & Project Setup
- Logging, Exception & Utils Modules
- Entire Project Notebook Experiment
- Project Workflows
- Data Ingestion Notebook Experiment
- Data Ingestion Final Implementation
- Data Validation Notebook Experiment
- Data Validation Final Implementation
- Data Transformation Notebook Experiment
- Data Transformation Final Implementation
- Model Trainer Notebook Experiment
- Model Trainer Final Implementation
- Model Evaluation Notebook Experiment
- Model Evaluation Final Implementation
- Prediction Pipeline & User App
- Project CI/CD Deployment on AWS
- Outro/ End of the Project
Taught by
Krish Naik
