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Rogerio Guimaraes

In this one-hour project, you will understand how Amazon Comprehend works and how you can use the power of Natual Language Processing, NLP, and Machine Learning to extract information and explore insights from text. You will learn how to use Amazon Comprehend to extract entities, people, sentiments, and other elements from text like Tweets, understand how the results are organized, manipulate the data and generate a report to explore the insights.

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In this one-hour project, you will understand how Amazon Comprehend works and how you can use the power of Natual Language Processing, NLP, and Machine Learning to extract information and explore insights from text. You will learn how to use Amazon Comprehend to extract entities, people, sentiments, and other elements from text like Tweets, understand how the results are organized, manipulate the data and generate a report to explore the insights.

Amazon Comprehend is a fully managed service and it is one of the most powerful Natural Language Processing engines in the market, so you can get up and running quickly, without having to train models from scratch.

Once you're done with this project, you will be able to use Amazon Comprehend to extract, analyze and explore insights in your documents in just a few steps.

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What's inside

Syllabus

Project Overview
In this one-hour project, you will understand how Amazon Comprehend works and how you can use the power of Natual Language Processing, NLP, and Machine Learning to extract information and explore insights from text. You will learn how to use Amazon Comprehend to extract entities, people, sentiments, and other elements from text like Tweets, understand how the results are organized, manipulate the data and generate a report to explore the insights. Amazon Comprehend is a fully managed service and it is one of the most powerful Natural Language Processing engines in the market, so you can get up and running quickly, without having to train models from scratch. Once you're done with this project, you will be able to use Amazon Comprehend to extract, analyze and explore insights in your documents in just a few steps.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Embraces industry best practices, standards and principles
Leverages Natural Language Processing, NLP, and Machine Learning
Teaches skills and knowledge that are highly relevant to the industry
Provides hands-on labs and interactive materials
Taught by an instructor who is recognized for their work in the topic
Develops a strong foundation for beginners

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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 Explore insights from text analysis using Amazon Comprehend with these activities:
Amazon Comprehend Tutorials
Follow guided tutorials to gain hands-on experience with Amazon Comprehend.
Browse courses on Amazon Comprehend
Show steps
  • Visit the Amazon Comprehend documentation page.
  • Choose a tutorial that aligns with your interests.
  • Follow the instructions provided in the tutorial.
NLP Exercises
Practice NLP techniques to reinforce your understanding of the concepts covered in the course.
Show steps
  • Find a dataset of text data.
  • Use a programming language of your choice to load the data and perform NLP tasks.
  • Extract key insights and patterns from the data.
Sentiment Analysis Exercises
Practice sentiment analysis techniques to improve your ability to detect emotions and opinions in text.
Browse courses on Sentiment Analysis
Show steps
  • Find a dataset of text data with sentiment labels.
  • Use a programming language of your choice to load the data and perform sentiment analysis tasks.
  • Evaluate the results and identify patterns in the data.
Five other activities
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Show all eight activities
Attend NLP Meetup
Expand your network and learn from others in the NLP community by attending meetups.
Show steps
  • Research NLP meetups in your area.
  • Attend a meetup and introduce yourself to others.
  • Participate in discussions and share your insights.
  • Follow up with people you meet and connect with them on LinkedIn.
NLP Study Group
Collaborate with peers to reinforce your understanding of NLP concepts and techniques.
Show steps
  • Find a group of peers who are also interested in NLP.
  • Meet regularly to discuss course materials, work on projects, and share ideas.
  • Provide feedback and support to each other.
NLP Summary Blog Post
Demonstrate your understanding of NLP by creating a blog post that summarizes the key concepts and applications.
Show steps
  • Research different NLP techniques and applications.
  • Outline the main points you want to cover in your blog post.
  • Write a draft of your blog post.
  • Edit and revise your blog post for clarity and accuracy.
NLP Case Studies
Explore real-world applications of NLP by reviewing case studies.
Browse courses on NLP Applications
Show steps
  • Identify case studies that are relevant to your interests.
  • Read through the case studies and identify the key challenges and solutions.
  • Analyze the results and discuss the implications for your own work.
NLP Project
Apply your NLP skills to a practical problem or project.
Show steps
  • Define the scope and objectives of your project.
  • Gather and prepare the necessary data.
  • Develop and implement an NLP solution using Amazon Comprehend.
  • Evaluate the results and identify areas for improvement.
  • Document your project in a report or presentation.

Career center

Learners who complete Explore insights from text analysis using Amazon Comprehend will develop knowledge and skills that may be useful to these careers:
Natural Language Processing Engineer
As an NLP Engineer, you can utilize Amazon Comprehend to build and deploy NLP pipelines for various applications. This course offers practical guidance on using the service to extract meaningful insights from text, empowering you to drive innovation in natural language processing.
Data Analyst
Amazon Comprehend helps Data Analysts extract and analyze key insights from large amounts of text data. This course provides a comprehensive overview of the service, enabling you to leverage its capabilities to improve data-driven decision-making and uncover hidden patterns in unstructured text.
Text Mining Analyst
For Text Mining Analysts, Amazon Comprehend provides a robust platform for extracting valuable information from large text datasets. This course equips you with the skills to use the service to identify trends, patterns, and insights, enabling you to gain a deeper understanding of your data.
Customer Success Manager
Customer Success Managers can use Amazon Comprehend to analyze customer feedback and identify opportunities for improvement. This course offers practical guidance on using the service to extract insights from support tickets, chat logs, and other customer interactions.
Machine Learning Engineer
Amazon Comprehend is a powerful tool for Machine Learning Engineers to build and deploy NLP models. This course provides hands-on experience in using the service to develop and evaluate NLP models, enabling you to enhance the accuracy and efficiency of your machine learning projects.
Data Scientist
Data Scientists can leverage Amazon Comprehend to enhance their data analysis capabilities. This course provides a comprehensive understanding of the service, empowering you to incorporate NLP techniques into your data science workflow and improve the accuracy and relevance of your insights.
Marketing Analyst
Marketing Analysts can utilize Amazon Comprehend to gain insights from customer feedback, social media data, and other text sources. This course offers practical guidance on using the service to identify trends, measure campaign effectiveness, and improve marketing strategies.
User Experience Researcher
User Experience Researchers can utilize Amazon Comprehend to gather insights from user feedback and improve product usability. This course offers practical guidance on using the service to extract sentiment, identify pain points, and design more user-friendly experiences.
Business Analyst
Business Analysts can benefit from Amazon Comprehend's ability to extract insights from text data. This course offers practical guidance on using the service to gather valuable information from customer feedback, market research, and other sources, enabling you to make informed business decisions.
Information Architect
Information Architects can use Amazon Comprehend to enhance the organization and accessibility of information. This course provides insights into using the service to extract metadata, classify documents, and improve search functionality.
Technical Writer
Technical Writers can leverage Amazon Comprehend to improve the accuracy and quality of their documentation. This course offers practical guidance on using the service to extract keywords, identify concepts, and ensure consistency in technical writing.
Product Manager
Product Managers can leverage Amazon Comprehend to gather insights from user feedback and reviews. This course provides a comprehensive understanding of the service, enabling you to use it to identify product pain points, prioritize feature development, and improve customer satisfaction.
Librarian
Librarians can leverage Amazon Comprehend to enhance their research and information retrieval capabilities. This course provides insights into using the service to extract metadata, classify documents, and improve library search functionality.
Content Strategist
Content Strategists can leverage Amazon Comprehend to analyze and optimize their content for better engagement and impact. This course provides insights into using the service to extract keywords, identify sentiment, and detect entities, empowering you to create highly effective content strategies.
Salesforce Administrator
Salesforce Administrators can utilize Amazon Comprehend to enhance their data management and reporting capabilities. This course provides insights into using the service to extract information from customer data, automate workflows, and improve sales processes.

Reading list

We've selected 12 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Explore insights from text analysis using Amazon Comprehend.
This textbook provides a comprehensive overview of natural language processing (NLP) using the Python programming language and the Natural Language Toolkit (NLTK) library. It covers various NLP tasks, including text classification, named entity recognition, and sentiment analysis, which are essential for understanding and extracting insights from text data.
Provides a comprehensive overview of statistical learning methods, including supervised and unsupervised learning, regression, classification, and clustering. It covers both theoretical concepts and practical applications in various domains.
Provides a comprehensive introduction to NLP, covering a wide range of topics from basic concepts to advanced techniques. It includes practical examples and exercises to help readers apply their knowledge.
Provides a comprehensive overview of pattern recognition and machine learning, covering topics such as supervised and unsupervised learning, feature selection, and model evaluation. It offers a theoretical foundation and practical insights into machine learning algorithms.
Comprehensive textbook that covers the theoretical foundations and practical applications of speech and language processing. Provides a thorough understanding of the core concepts and algorithms used in NLP, including text analysis, machine translation, and speech recognition.
Provides a comprehensive overview of machine learning techniques for text, covering topics such as text classification, text clustering, and natural language generation. It includes both theoretical and practical aspects of machine learning for text.
Provides a comprehensive introduction to information theory, inference, and learning algorithms, which are fundamental concepts in machine learning and natural language processing. It covers topics such as probability theory, Bayesian inference, and supervised learning.
Focuses on deep learning techniques for NLP, providing a detailed overview of neural network architectures and algorithms used for tasks such as text classification, question answering, and machine translation.
Provides a comprehensive introduction to information retrieval, including techniques for document retrieval, text classification, and web search. It covers both the theoretical foundations and practical applications of information retrieval.
Classic in the field of NLP and provides a rigorous foundation in the statistical methods and models used for natural language processing. It covers topics such as language modeling, machine translation, and information retrieval.

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