Overview
In this module, we will learn about natural language processing of text. In particular, we will study natural language processing of review text regarding analyzing the sentiment and objectivity. For that we will use the TextBlob module. The other topic of this module is machine learning. We are using the scikit-learn module which provides the most important machine learning tools which allow us to analyze data and predict future results. Learning Objectives
By the end of this course, you will be able to:
CO1: Identify industry-standard approaches to organization, storage, manipulation, analysis, and visualization of big data
CO2: Wrangle raw data from different sources and formats
CO3: Write data science programs in Python through an object-oriented approach using common data science packages
CO4: Analyze data and results through statistical and visual analysis
CO5: Investigate data science problems involving big data
By the end of this module, you will be able to:
MO 6.1 Use TextBlob to tokenize natural language (supports CO1, CO2, CO3, CO4, CO5)
MO 6.2 Create a word cloud visualization using Python programming (supports CO4)
MO 6.3 Conduct a sentiment analysis on natural language (supports CO4)
MO 6.4 Understand the principles of machine learning
MO 6.5 Conduct a simple data analysis using machine learning tools which come with the scikit-learn library (supports CO4)
MO 6.7 Visualize accuracy of machine learning models using heat maps (supports CO1, CO2, CO3, CO4, CO5)