Advanced NLP with Python for Machine Learning

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Gwendolyn Stripling

1:26:19

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01 - Introduction

01 - Elevate Your NLP expertise using Python and machine learning.mp4

00:51

02 - What you should know.mp4

00:19

03 - How to use the challenge exercise files.mp4

01:35

02 - 1. Introduction to NLP Libraries

01 - Overview of natural language processing.mp4

04:09

02 - Evolution of natural language processing.mp4

05:46

03 - Natural language processing libraries.mp4

02:09

03 - 2. Review NLP and Python Basics

01 - Introduction to spaCy.mp4

04:18

02 - Challenge Build a spaCy processing pipeline.mp4

01:23

03 - Solution Build a processing pipeline.mp4

04:16

04 - 3. Using spaCy for Customer Feedback Analysis

01 - Analyze customer feedback using spaCy.mp4

04:38

02 - The spaCy processing pipeline.mp4

03:30

03 - Challenge Analyze customer feedback.mp4

00:40

04 - Solution Analyze customer feedback.mp4

02:34

05 - 4. Modern NLP Transformers and Large Language Models

01 - Modern natural language processing.mp4

03:44

02 - Transformers neural networks.mp4

06:18

03 - Large language models BERT, GPT.mp4

03:23

04 - Challenge Sentiment analysis using DistilBERT.mp4

00:46

05 - Solution Sentiment analysis using DistilBERT.mp4

03:22

06 - 5. Methods That Improve LLM Performance

01 - Methods that improve LLM performance.mp4

05:23

02 - Supervised fine-tuning.mp4

02:21

03 - Fine-tuning methods.mp4

06:09

04 - Retrieval-augmented generation (RAG).mp4

03:05

05 - Parameter-efficient fine-tuning (PEFT).mp4

05:10

06 - Challenge Parameter-efficient fine-tuning with LoRa.mp4

01:03

07 - Solution Parameter-efficient fine-tuning with LoRa.mp4

08:08

07 - Conclusion

01 - Next steps.mp4

01:19

Description

This course is for anyone who wants to learn more advanced NLP methods. Instructor Gwendolyn Stripling, PhD, begins with a look at the fundamental concepts and principles of NLP, including the evolution and significance of natural language processing. She then reviews some NLP and Python basics—and introduces the NLP library spaCy—before jumping into more modern techniques and advancements in natural language processing using Transformer Models like GPT and BERT. Methods such as supervised fine-tuning, parameter efficient fine-tuning (PEFT), and retrieval-augmented generation (RAG) give you the foundational knowledge you need to improve large language model (LLM) performance. Learn the ways you can apply NLP in your applications and day-to-day, including how to analyze customer sentiments Each chapter ends with a challenge and solution, so you can test your knowledge as you go.

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Python

Machine Learning

Gwendolyn Stripling

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LinkedIn Learning is an American online learning provider. It provides video courses taught by industry experts in software, creative, and business skills. It is a subsidiary of LinkedIn. All the courses on LinkedIn fall into four categories: Business, Creative, Technology and Certifications. It was founded in 1995 by Lynda Weinman as Lynda.com before being acquired by LinkedIn in 2015. Microsoft acquired LinkedIn in December 2016.