Course Highlights
  • Learn to work with Text Files with Python
  • Learn how to work with PDF files in Python
  • Utilize Regular Expressions for pattern searching in text
  • Use Spacy for ultra fast tokenization
  • Learn about Stemming and Lemmatization
  • Understand Vocabulary Matching with Spacy
  • Use Part of Speech Tagging to automatically process raw text files
  • Understand Named Entity Recognition
  • Visualize POS and NER with Spacy
  • Use SciKit-Learn for Text Classification
  • Use Latent Dirichlet Allocation for Topic Modelling
  • Learn about Non-negative Matrix Factorization
  • Use the Word2Vec algorithm
  • Use NLTK for Sentiment Analysis
  • Use Deep Learning to build out your own chat bot
Curriculum

5 Topics
Course Overview - DO NOT SKIP THIS LECTURE PLEASE. IMPORTANT INFO HERE!
Quick Check
Curriculum Overview
Installation and Setup Lecture
FAQ - Frequently Asked Questions

8 Topics
Introduction to Python Text Basics
Working with Text Files with Python - Part One
Working with Text Files with Python - Part Two
Working with PDFs
Regular Expressions Part One
Regular Expressions Part Two
Python Text Basics - Assessment Overview
Python Text Basics - Assessment Solutions

13 Topics
Introduction to Natural Language Processing
Spacy Setup and Overview
What is Natural Language Processing?
Spacy Basics
Tokenization - Part One
Tokenization - Part Two
Stemming
Lemmatization
Stop Words
Phrase Matching and Vocabulary - Part One
Phrase Matching and Vocabulary - Part Two
NLP Basics Assessment Overview
NLP Basics Assessment Solution

9 Topics
Introduction to Section on POS and NER
Part of Speech Tagging
Visualizing Part of Speech
Named Entity Recognition - Part One
Named Entity Recognition - Part Two
Visualizing Named Entity Recognition
Sentence Segmentation
Part Of Speech Assessment
Part Of Speech Assessment - Solutions

13 Topics
Introduction to Text Classification
Machine Learning Overview
Classification Metrics
Confusion Matrix
Scikit-Learn Primer - How to Use SciKit-Learn
Scikit-Learn Primer - Code Along Part One
Scikit-Learn Primer - Code Along Part Two
Text Feature Extraction Overview
Text Feature Extraction - Code Along Implementations
Text Feature Extraction - Code Along - Part Two
Text Classification Code Along Project
Text Classification Assessment Overview
Text Classification Assessment Solutions

8 Topics
Introduction to Semantics and Sentiment Analysis
Overview of Semantics and Word Vectors
Semantics and Word Vectors with Spacy
Sentiment Analysis Overview
Sentiment Analysis with NLTK
Sentiment Analysis Code Along Movie Review Project
Sentiment Analysis Project Assessment
Sentiment Analysis Project Assessment - Solutions

9 Topics
Introduction to Topic Modeling Section
Overview of Topic Modeling
Latent Dirichlet Allocation Overview
Latent Dirichlet Allocation with Python - Part One
Latent Dirichlet Allocation with Python - Part Two
Non-negative Matrix Factorization Overview
Non-negative Matrix Factorization with Python
Topic Modeling Project - Overview
Topic Modeling Project - Solutions

15 Topics
Introduction to Deep Learning for NLP
The Basic Perceptron Model
Introduction to Neural Networks
Keras Basics - Part One
Keras Basics - Part Two
Recurrent Neural Network Overview
LSTMs GRU and Text Generation
Text Generation with LSTMs with Keras and Python - Part One
Text Generation with LSTMs with Keras and Python - Part Two
Text Generation with LSTMS with Keras - Part Three
Chat Bots Overview
Creating Chat Bots with Python - Part One
Creating Chat Bots with Python - Part Two
Creating Chat Bots with Python - Part Three
Creating Chat Bots with Python - Part Four

1 Topic
BONUS LECTURE

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NLP - Natural Language Processing with Python

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