NLP - Machine Learning Online Course
NLP - Machine Learning Online Course
This course is an essential resource for technical professionals looking to excel in the rapidly evolving field of natural language processing.
The course will start with an introduction and then take you through the rest of the sections. Each section begins with a problem description, followed by intuitive explanations of algorithms like Naive Bayes, logistic regression, and Latent Dirichlet Allocation. You'll engage with practical exercises designed to reinforce your understanding, and apply these techniques using Python in a hands-on manner.
By the end, you'll have a robust understanding of various NLP techniques and the confidence to apply them in real-world scenarios.
Course Curriculum
Welcome
- Introduction and Outline
- Special Offer
Getting Set Up
- Where To Get the Code
- How To Succeed in This Course
Spam Detection
- Spam Detection - Problem Description
- Naive Bayes Intuition
- Spam Detection - Exercise Prompt
- Aside: Class Imbalance, ROC, AUC, and F1 Score (pt 1)
- Aside: Class Imbalance, ROC, AUC, and F1 Score (pt 2)
- Spam Detection in Python
Sentiment Analysis
- Sentiment Analysis - Problem Description
- Logistic Regression Intuition (pt 1)
- Multiclass Logistic Regression (pt 2)
- Logistic Regression Training and Interpretation
- Sentiment Analysis - Exercise Prompt
- Sentiment Analysis in Python (pt 1)
- Sentiment Analysis in Python (pt 2)
Text Summarization
- Text Summarization Section Introduction
- Text Summarization Using Vectors
- Text Summarization Exercise Prompt
- Text Summarization in Python
- TextRank Intuition
- TextRank - How It Really Works (Advanced)
- TextRank Exercise Prompt (Advanced)
- TextRank in Python (Advanced)
- Text Summarization in Python - The Easy Way (Beginner)
- Text Summarization Section Summary
Topic Modeling
- Topic Modeling Section Introduction
- Latent Dirichlet Allocation (LDA) - Essentials
- LDA - Code Preparation
- LDA - Maybe Useful Picture (Optional)
- Latent Dirichlet Allocation (LDA) - Intuition (Advanced)
- Topic Modeling with Latent Dirichlet Allocation (LDA) in Python
- Non-Negative Matrix Factorization (NMF) Intuition
- Topic Modeling with Non-Negative Matrix Factorization (NMF) in Python
- Topic Modeling Section Summary
Latent Semantic Analysis (Latent Semantic Indexing)
- LSA / LSI Section Introduction
- SVD (Singular Value Decomposition) Intuition
- LSA / LSI: Applying SVD to NLP
- Latent Semantic Analysis / Latent Semantic Indexing in Python
- LSA / LSI Exercises
