Introduction to Text Classification in R with quanteda from Coursera

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Syllabus

Project Overview

By the end of this project, you will learn how to import textual data stored in raw text files into R, turn these files into a corpus (a collection of textual documents), reshape them into paragraphs from documents and tokenize the text all using the R software package quanteda. You will then learn how to classify the texts using the Naive Bayes algorithm. At the end of this project, among other things, you will have imported documents, reshaped texts from documents to paragraphs, turned your texts into a machine readable format, and classified presidential concession speeches by political party. You will also learn to assess the accuracy of the predictions. This guided project is for beginners interested in quantitative text analysis in R. It assumes no knowledge of textual analysis and focuses on exploring textual data (US Presidential Concession Speeches). Users should have a basic understanding of the statistical programming language R. By the end of the exercise, learners will know how to load textual data into R, summarize the data using descriptive quantities of interest, turn text into tokens, and do simple text classification.

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Develops knowledge of importing textual data into R, turning texts into a machine-readable format, and classifying presidential concession speeches by political party

Builds a foundation for understanding quantitative text analysis in R

Teaches how to assess the accuracy of predictions made through the Naive Bayes algorithm

Assumes no knowledge of textual analysis, making it accessible to beginners

Requires a basic understanding of the R programming language

Focuses on exploring textual data specifically from US Presidential Concession Speeches

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Introduction to Text Classification in R with quanteda with these activities:

Review basic R programming concepts

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Prepare yourself for the course by reviewing the fundamentals of R programming, ensuring a solid foundation for understanding the upcoming material.

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Go over R syntax and data types
Refresh your knowledge of data manipulation functions

Understanding Natural Language Processing with Python and R

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Strengthen your foundation by reviewing this comprehensive resource on natural language processing techniques, complementing the course material and expanding your knowledge.

View Natural Language Processing with Python:... on Amazon

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Read the chapters related to text analysis
Work through the provided exercises
Apply the concepts to a small text analysis project

Compile a glossary of text analysis terms

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Enhance your understanding by creating a glossary of key text analysis terms, solidifying your grasp of the essential concepts and improving retention.

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Identify key terms from the course material and external resources
Define each term clearly and concisely
Organize the terms alphabetically or by category

Four other activities

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Explore the quanteda package

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Familiarize yourself with the basics of the quanteda package by following tutorials, allowing you to better comprehend the course material.

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Identify a beginner-friendly tutorial on the quanteda package
Follow the tutorial to import a text file
Create a corpus and reshape data using quanteda functions
Tokenize and lemmatize the text

Practice text analysis using the Naive Bayes algorithm

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Reinforce your understanding of the Naive Bayes algorithm by practicing text classification, solidifying the concepts covered in the course.

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Find a dataset with labeled text data
Load the data into R and split it into training and testing sets
Train a Naive Bayes model on the training data
Evaluate the model's performance on the test data

Participate in a text analysis competition

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Challenge yourself and test your skills by participating in a text analysis competition, offering an opportunity to apply your knowledge in a practical setting.

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Identify a relevant text analysis competition (e.g., Kaggle, DrivenData)
Gather a team or participate individually
Apply the concepts learned in the course to build a model
Submit your solution and analyze the results

Create a visualization of presidential concession speeches

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Enhance your comprehension of the data by creating a visualization of presidential concession speeches, reinforcing your knowledge and fostering critical analysis.

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Choose a visualization technique (e.g., word cloud, bar chart)
Extract the relevant data from the speeches
Create the visualization using a data visualization tool (e.g., ggplot2)
Analyze and interpret the visualization

Career center

Learners who complete Introduction to Text Classification in R with quanteda will develop knowledge and skills that may be useful to these careers:

Natural Language Processing Researcher

As a NLP Researcher, you will research and develop natural language processing algorithms and techniques. In addition to focusing on understanding spoken and written language, NLP researchers also work to enable computers to communicate with humans in a natural way. Using foundational knowledge in text analytics, such as that learned through the Introduction to Text Classification in R with quanteda course, you will be able to contribute to the development of new NLP technologies.

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Data Analyst

Data Analysts are responsible for collecting, cleaning, and analyzing data to identify trends and patterns. Data Analysts may focus on statistical analysis, data mining, or machine learning, each of which has applications in text analytics. With the text classification skills learned in the Introduction to Text Classification in R with quanteda course, you will be positioned well to help make sense of the large amounts of data that organizations collect.

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Machine Learning Engineer

Building, deploying, and maintaining machine learning models are the core responsibilities of Machine Learning Engineers. Some Machine Learning Engineers focus on NLP, in which case they concentrate on developing models that can process and understand human language. The Introduction to Text Classification in R with quanteda course can be a valuable asset for those interested in working in this specialized area of machine learning.

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Computational Linguist

Computational Linguists apply computational techniques to the study of language, helping to bridge the gap between computer science and linguistics. With a strong foundation in text analytics, such as that developed in the Introduction to Text Classification in R with quanteda course, Computational Linguists can pursue a wide range of research interests, such as natural language processing, machine translation, and speech recognition.

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Information Architect

Information Architects design and organize information systems to make them easy to find and use. To do so, they need to have a strong understanding of how people interact with information, which is why many Information Architects have backgrounds in library science or linguistics. The Introduction to Text Classification in R with quanteda course could be useful for those who wish to specialize in organizing textual information.

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User Experience Researcher

User Experience Researchers study how people interact with products and services in order to improve their usability. This often involves collecting and analyzing data on user behavior, which can include text data. The Introduction to Text Classification in R with quanteda course can be a good way to develop the skills needed to collect and analyze this type of data.

See salaries and explore the career path for User Experience Researcher

Content Strategist

Content Strategists help organizations create and manage content that is effective and engaging. This often involves understanding the needs of the target audience and developing content that is tailored to those needs. The Introduction to Text Classification in R with quanteda course can be a good way to develop the skills needed to analyze and understand text data, which can be useful for developing content strategies.

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Market Researcher

Market Researchers collect and analyze data to understand consumer behavior and market trends. This often involves collecting and analyzing text data, such as social media data or customer reviews. The Introduction to Text Classification in R with quanteda course can be a good way to develop the skills needed to collect and analyze this type of data.

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Public Relations Specialist

Public Relations Specialists manage the public image of organizations and individuals. This often involves writing and distributing press releases, managing social media accounts, and responding to media inquiries. The Introduction to Text Classification in R with quanteda course can be a good way to develop the skills needed to analyze and understand text data, which can be useful for developing public relations strategies.

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Community Manager

Community Managers manage online communities, such as social media groups and forums. This often involves creating and curating content, moderating discussions, and responding to user inquiries. The Introduction to Text Classification in R with quanteda course can be a good way to develop the skills needed to analyze and understand text data, which can be useful for developing community management strategies.

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Technical Writer

Technical Writers create and maintain documentation for software, hardware, and other technical products. This documentation can include user manuals, white papers, and technical reports. The Introduction to Text Classification in R with quanteda course can be a good way to develop the skills needed to analyze and understand text data, which can be useful for developing technical documentation.

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Knowledge Manager

Knowledge Managers create and manage knowledge repositories for organizations. This often involves collecting, organizing, and disseminating information from a variety of sources. The Introduction to Text Classification in R with quanteda course can be a good way to develop the skills needed to analyze and understand text data, which can be useful for developing knowledge management strategies.

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Digital Marketing Specialist

Digital Marketing Specialists develop and implement digital marketing campaigns for businesses. This often involves creating and managing content, running social media ads, and tracking website traffic. The Introduction to Text Classification in R with quanteda course can be a good way to develop the skills needed to analyze and understand text data, which can be useful for developing digital marketing strategies.

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Business Analyst

Business Analysts analyze business needs and develop solutions to improve efficiency and productivity. This often involves collecting and analyzing data, including text data. The Introduction to Text Classification in R with quanteda course can be a good way to develop the skills needed to collect and analyze this type of data.

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Software Developer

Software Developers design, develop, and maintain software applications. This often involves working with text data, such as source code or user documentation. The Introduction to Text Classification in R with quanteda course may be useful for those who wish to specialize in developing software applications that involve text data.

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Introduction to Text Classification in R with quanteda

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Solid text classification course

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