Course Details
Course Details
What You'll Learn
Topic 1 Overview of Text Mining and Text Analytics
Introduction to Natural Language Processing (NLP)
Applications of Text Analytics and Text Mining for Business Intelligence
Cross-Industry Standard Process for Data Mining (CRISP-DM)
Topic 2: Text Cleaning and Pre-processing
Install Python NLTK Package
Read In Text Corpus
Remove Punctuation and Stop Words
Pre-process Text using Tokenization, Stemming, Lemmatization
Vectorize Text using Term Frequency (TF) Vectorization, N-gram and Inverse-Document Frequency (TF-IDF)
Topic 3 Text Analytics
Part of Speech (POS) Tagging
Name Entity Recognition (NER)
Text Link Analysis and Feature Engineering
Topic 4: Sentimental Analysis
Overview of Machine Learning
Install Python Scikit Learn Package
Build a Machine Learning Model for Sentimental Analysis
Model Evaluation
Topic 5: Text Summarization
Summarize Sentiment Analysis
Visualize Text Summarization
Course Info
Prerequisite
This is an intermediate level course. The following prerequisite is assumed
Software Requirement
Please download and install the following software prior to the class
- Python 3.x https://www.python.org/downloads/
- Sublime Text 3 https://www.sublimetext.com/3
- Pycharm https://www.jetbrains.com/pycharm/download/
Job Roles
Job Roles
- Aspiring Software Developer
- Data Analyst
- Web Developer
- Automation Engineer
- Data Scientist
- System Administrator
- Bioinformatics Specialist
- Research Scientist
- Finance Professional
- Machine Learning Enthusiast
- GIS (Geographic Information System) Specialist
- IT Consultant
- Network Engineer
- Database Administrator
- Tech Entrepreneur.