IIRF Online > Development > Data Science > Natural Language Processing > Data Science: Natural Language Processing (NLP) in Python
Data Science: Natural Language Processing (NLP) in Python by Udemy
Applications: decrypting ciphers, spam detection, sentiment analysis, article spinners, and latent semantic analysis.
Course Highlights
- Write your own cipher decryption algorithm using genetic algorithms and language modeling with Markov models
- Write your own spam detection code in Python
- Write your own sentiment analysis code in Python
- Perform latent semantic analysis or latent semantic indexing in Python
- Have an idea of how to write your own article spinner in Python
Skills you will learn!
Curriculum
3 Topics
Introduction and Outline
Why Learn NLP?
The Central Message of this Course (Big Picture Perspective)
3 Topics
How to Succeed in this Course
Where to get the code and data
How to Open Files for Windows Users
11 Topics
Machine Learning: Section Introduction
What is Classification?
Classification in Code
What is Regression?
Regression in Code
What is a Feature Vector?
Machine Learning is Nothing but Geometry
All Data is the Same
Comparing Different Machine Learning Models
Machine Learning and Deep Learning: Future Topics
Section Summary
13 Topics
Markov Models Section Introduction
The Markov Property
The Markov Model
Probability Smoothing and Log-Probabilities
Building a Text Classifier (Theory)
Building a Text Classifier (Exercise Prompt)
Building a Text Classifier (Code pt 1)
Building a Text Classifier (Code pt 2)
Language Model (Theory)
Language Model (Exercise Prompt)
Language Model (Code pt 1)
Language Model (Code pt 2)
Markov Models Section Summary
12 Topics
Section Introduction
Ciphers
Language Models
Genetic Algorithms
Code Preparation
Code pt 1
Code pt 2
Code pt 3
Code pt 4
Code pt 5
Code pt 6
Section Conclusion
11 Topics
Build your own spam detector - description of data
Build your own spam detector using Naive Bayes and AdaBoost - the code
Key Takeaway from Spam Detection Exercise
Naive Bayes Concepts
AdaBoost Concepts
Other types of features
Spam Detection FAQ (Remedial #1)
What is a Vector? (Remedial #2)
SMS Spam Example
SMS Spam in Code
Suggestion Box
7 Topics
Description of Sentiment Analyzer
Logistic Regression Review
Preprocessing: Tokenization
Preprocessing: Tokens to Vectors
Sentiment Analysis in Python using Logistic Regression
Sentiment Analysis Extension
How to Improve Sentiment Analysis & FAQ
4 Topics
NLTK Exploration: POS Tagging
NLTK Exploration: Stemming and Lemmatization
NLTK Exploration: Named Entity Recognition
Want more NLTK?
5 Topics
Latent Semantic Analysis - What does it do?
SVD - The underlying math behind LSA
Latent Semantic Analysis in Python
What is Latent Semantic Analysis Used For?
Extending LSA
6 Topics
Article Spinning Introduction and Markov Models
Trigram Model
More about Language Models
Precode Exercises
Writing an article spinner in Python
Article Spinner Extension Exercises
1 Topic
What we didn't talk about
3 Topics
Pre-Installation Check
Anaconda Environment Setup
How to install Numpy Scipy Matplotlib Pandas IPython Theano and TensorFlow
4 Topics
How to Code by Yourself (part 1)
How to Code by Yourself (part 2)
Proof that using Jupyter Notebook is the same as not using it
Python 2 vs Python 3
4 Topics
How to Succeed in this Course (Long Version)
Is this for Beginners or Experts? Academic or Practical? Fast or slow-paced?
Machine Learning and AI Prerequisite Roadmap (pt 1)
Machine Learning and AI Prerequisite Roadmap (pt 2)
2 Topics
What is the Appendix?
BONUS
Data Science: Natural Language Processing (NLP) in Python
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