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Sebastian Thrun,
Cezanne Camacho,
Jay Alammar,
Alexis Cook,
Luis Serrano,
Juan Delgado,
and
Ortal Arel
Learn how to create a simple neural network for analyzing the sentiment (bad or good) in the text of movie reviews.
Register for this course and see more details by visiting:
OpenCourser.com/course/z7vgs9/text
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What's inside
Syllabus
In this lesson, Andrew Trask, the author of Grokking Deep Learning, will walk you through using neural networks for sentiment analysis.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Suitable for students pursuing a career in artificial intelligence or machine learning
Covers a range of foundational concepts in natural language processing
Led by instructors who are recognized for their contributions to the field
Emphasizes hands-on learning through practical exercises and projects
Suitable for both beginners and those looking to strengthen their foundation in natural language processing
May require students to have some prior knowledge in Python programming
Save this course
Save Text Sentiment Analysis to your list so you can find it easily later:
Save
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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 Text Sentiment Analysis with these
activities:
Compile Resources on Sentiment Analysis and Movie Reviews
Show steps
Enhance your knowledge and expand your resources by gathering and organizing relevant materials on sentiment analysis and movie reviews.
Browse courses on
Sentiment Analysis
Show steps
-
Search for articles, tutorials, datasets, and other resources related to sentiment analysis.
-
Evaluate the quality and relevance of each resource.
-
Categorize and organize the resources based on topic or theme.
-
Create a repository or documentation that compiles the gathered resources.
Follow a Guided Tutorial on Building a Movie Review Sentiment Analyzer
Show steps
Supplement your understanding of sentiment analysis by following a step-by-step tutorial that guides you through building a movie review sentiment analyzer using neural networks.
Browse courses on
Sentiment Analysis
Show steps
-
Identify a suitable tutorial that aligns with your skill level.
-
Gather the necessary resources and prerequisites.
-
Follow the tutorial instructions carefully, implementing each step.
-
Test and refine your sentiment analyzer based on the tutorial's guidance.
Practice Sentiment Analysis on Movie Reviews
Show steps
Reinforce your understanding of sentiment analysis techniques by working through practice problems involving movie reviews.
Browse courses on
Sentiment Analysis
Show steps
-
Load and pre-process the movie review dataset.
-
Implement a simple neural network model for sentiment analysis.
-
Train and evaluate your model on the movie review dataset.
-
Analyze the performance of your model and identify areas for improvement.
Two other activities
Expand to see all activities and additional details
Show all five activities
Develop a Case Study on Sentiment Analysis for Movie Reviews
Show steps
Deepen your understanding of sentiment analysis by conducting a case study that investigates the application of sentiment analysis techniques to movie reviews.
Browse courses on
Sentiment Analysis
Show steps
-
Define the research question and objectives of your case study.
-
Collect and analyze a dataset of movie reviews.
-
Apply sentiment analysis techniques to the dataset and interpret the results.
-
Draw conclusions and make recommendations based on your findings.
-
Write a comprehensive report that documents your case study.
Start a Project to Apply Sentiment Analysis to a Real-World Problem
Show steps
Gain practical experience by initiating a project that utilizes sentiment analysis techniques to address a real-world problem.
Browse courses on
Sentiment Analysis
Show steps
-
Identify a real-world problem or domain that can benefit from sentiment analysis.
-
Gather and analyze a dataset relevant to the problem domain.
-
Design and implement a sentiment analysis solution that addresses the problem.
-
Evaluate the performance of your solution and make improvements as needed.
-
Deploy or present your solution to demonstrate its impact.
Compile Resources on Sentiment Analysis and Movie Reviews
Show steps
Enhance your knowledge and expand your resources by gathering and organizing relevant materials on sentiment analysis and movie reviews.
Browse courses on
Sentiment Analysis
Show steps
Show steps
Show steps
- Search for articles, tutorials, datasets, and other resources related to sentiment analysis.
- Evaluate the quality and relevance of each resource.
- Categorize and organize the resources based on topic or theme.
- Create a repository or documentation that compiles the gathered resources.
Follow a Guided Tutorial on Building a Movie Review Sentiment Analyzer
Show steps
Supplement your understanding of sentiment analysis by following a step-by-step tutorial that guides you through building a movie review sentiment analyzer using neural networks.
Browse courses on
Sentiment Analysis
Show steps
Show steps
Show steps
- Identify a suitable tutorial that aligns with your skill level.
- Gather the necessary resources and prerequisites.
- Follow the tutorial instructions carefully, implementing each step.
- Test and refine your sentiment analyzer based on the tutorial's guidance.
Practice Sentiment Analysis on Movie Reviews
Show steps
Reinforce your understanding of sentiment analysis techniques by working through practice problems involving movie reviews.
Browse courses on
Sentiment Analysis
Show steps
Show steps
Show steps
- Load and pre-process the movie review dataset.
- Implement a simple neural network model for sentiment analysis.
- Train and evaluate your model on the movie review dataset.
- Analyze the performance of your model and identify areas for improvement.
Two other activities
Expand to see all activities and additional details
Show all five activities
Develop a Case Study on Sentiment Analysis for Movie Reviews
Show steps
Deepen your understanding of sentiment analysis by conducting a case study that investigates the application of sentiment analysis techniques to movie reviews.
Browse courses on
Sentiment Analysis
Show steps
Show steps
Show steps
- Define the research question and objectives of your case study.
- Collect and analyze a dataset of movie reviews.
- Apply sentiment analysis techniques to the dataset and interpret the results.
- Draw conclusions and make recommendations based on your findings.
- Write a comprehensive report that documents your case study.
Start a Project to Apply Sentiment Analysis to a Real-World Problem
Show steps
Gain practical experience by initiating a project that utilizes sentiment analysis techniques to address a real-world problem.
Browse courses on
Sentiment Analysis
Show steps
Show steps
Show steps
- Identify a real-world problem or domain that can benefit from sentiment analysis.
- Gather and analyze a dataset relevant to the problem domain.
- Design and implement a sentiment analysis solution that addresses the problem.
- Evaluate the performance of your solution and make improvements as needed.
- Deploy or present your solution to demonstrate its impact.
Career center
Learners who complete Text Sentiment Analysis will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
As a Machine Learning Engineer, you can work on building models that analyze text data, including sentiment analysis models. This course provides a great introduction to the fundamentals of sentiment analysis and neural networks, which are essential for building these models. You will learn how to design, train, and evaluate a sentiment analysis model, which is a valuable skill for any Machine Learning Engineer.
Natural Language Processing Engineer
Natural Language Processing Engineer
As a Natural Language Processing Engineer, you must build and maintain models that understand and generate human language. This course provides an overview of sentiment analysis, which is a key area of Natural Language Processing. You will learn how to build a sentiment analysis model, which is a valuable skill for any Natural Language Processing Engineer.
Data Scientist
Data Scientist
As a Data Scientist, you may need to analyze text data to extract insights. This course can help you build a foundation in sentiment analysis, which is a key skill for text analysis. You will learn how to use neural networks to analyze sentiment in text data, which is a valuable skill for any Data Scientist.
Software Engineer
Software Engineer
As a Software Engineer, you may need to develop applications that incorporate sentiment analysis. This course can help you build a foundation in sentiment analysis, which is a key area of Natural Language Processing. You will learn how to build a sentiment analysis model, which is a valuable skill for any Software Engineer who wants to work on Natural Language Processing applications.
Technical Writer
Technical Writer
As a Technical Writer, you may need to analyze customer feedback to understand sentiment. This course can help you build a foundation in sentiment analysis, which is a key skill for understanding customer needs. You will learn how to build a sentiment analysis model, which is a valuable skill for any Technical Writer who wants to create effective documentation.
Customer Success Manager
Customer Success Manager
As a Customer Success Manager, you may need to analyze customer feedback to understand sentiment. This course can help you build a foundation in sentiment analysis, which is a key skill for understanding customer needs. You will learn how to build a sentiment analysis model, which is a valuable skill for any Customer Success Manager who wants to build successful relationships with customers.
Market Researcher
Market Researcher
As a Market Researcher, you may need to analyze text data to understand customer sentiment. This course can help you build a foundation in sentiment analysis, which is a key skill for understanding market trends. You will learn how to build a sentiment analysis model, which is a valuable skill for any Market Researcher who wants to conduct effective research.
Public relations manager
Public relations manager
As a Public Relations Manager, you may need to analyze customer feedback to understand sentiment. This course can help you build a foundation in sentiment analysis, which is a key skill for understanding customer needs. You will learn how to build a sentiment analysis model, which is a valuable skill for any Public Relations Manager who wants to build successful relationships with the public.
Social Media Manager
Social Media Manager
As a Social Media Manager, you may need to analyze customer feedback to understand sentiment. This course can help you build a foundation in sentiment analysis, which is a key skill for understanding customer needs. You will learn how to build a sentiment analysis model, which is a valuable skill for any Social Media Manager who wants to build successful campaigns.
Customer Service Representative
Customer Service Representative
As a Customer Service Representative, you may need to analyze customer feedback to understand sentiment. This course can help you build a foundation in sentiment analysis, which is a key skill for understanding customer needs. You will learn how to build a sentiment analysis model, which is a valuable skill for any Customer Service Representative who wants to provide excellent customer service.
Marketing Manager
Marketing Manager
As a Marketing Manager, you may need to analyze customer feedback to understand sentiment. This course can help you build a foundation in sentiment analysis, which is a key skill for understanding customer needs. You will learn how to build a sentiment analysis model, which is a valuable skill for any Marketing Manager who wants to build successful campaigns.
Content Writer
Content Writer
As a Content Writer, you may need to analyze customer feedback to understand sentiment. This course can help you build a foundation in sentiment analysis, which is a key skill for understanding customer needs. You will learn how to build a sentiment analysis model, which is a valuable skill for any Content Writer who wants to create effective content.
Sales Manager
Sales Manager
As a Sales Manager, you may need to analyze customer feedback to understand sentiment. This course can help you build a foundation in sentiment analysis, which is a key skill for understanding customer needs. You will learn how to build a sentiment analysis model, which is a valuable skill for any Sales Manager who wants to build successful relationships with customers.
Business Analyst
Business Analyst
As a Business Analyst, you may need to analyze text data to understand customer sentiment. This course can help you build a foundation in sentiment analysis, which is a key skill for understanding customer feedback. You will learn how to build a sentiment analysis model, which is a valuable skill for any Business Analyst who wants to work on customer insights.
Product Manager
Product Manager
As a Product Manager, you may need to analyze customer feedback to understand sentiment. This course can help you build a foundation in sentiment analysis, which is a key skill for understanding customer needs. You will learn how to build a sentiment analysis model, which is a valuable skill for any Product Manager who wants to build successful products.
For more career information including salaries, visit:
OpenCourser.com/course/z7vgs9/text
Reading list
We've selected nine 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
Text Sentiment Analysis.
Provides a comprehensive overview of machine learning with R, covering the fundamentals of the field as well as advanced topics such as machine learning and deep learning. It valuable resource for students and researchers interested in learning more about machine learning with R.
Save
Provides a comprehensive overview of deep learning, covering the fundamentals of the field as well as advanced topics such as convolutional neural networks and recurrent neural networks. It valuable resource for students and researchers interested in learning more about deep learning.
Provides a comprehensive introduction to natural language processing, covering the fundamentals of the field as well as advanced topics such as machine learning and deep learning. It valuable resource for students and researchers interested in learning more about NLP.
Provides a comprehensive overview of sentiment analysis and opinion mining, covering the fundamentals of the field as well as advanced topics such as machine learning and deep learning. It valuable resource for students and researchers interested in learning more about sentiment analysis and opinion mining.
Save
Provides a comprehensive overview of text mining with R, covering the fundamentals of the field as well as advanced topics such as machine learning and deep learning. It valuable resource for students and researchers interested in learning more about text mining with R.
Provides a comprehensive overview of natural language processing, covering the fundamentals of the field as well as advanced topics such as machine learning and deep learning. It valuable resource for students and researchers interested in learning more about NLP.
Save
Provides a comprehensive overview of machine learning for text, covering the fundamentals of the field as well as advanced topics such as machine learning and deep learning. It valuable resource for students and researchers interested in learning more about machine learning for text.
Provides a comprehensive overview of deep learning with Python, covering the fundamentals of the field as well as advanced topics such as machine learning and deep learning. It valuable resource for students and researchers interested in learning more about deep learning with Python.
Provides a clear and concise introduction to deep learning, using intuitive explanations and visual examples to make the concepts easy to understand. It great resource for beginners who want to learn more about deep learning without getting bogged down in the details.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/z7vgs9/text
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Time
120 hours
Level
Advanced
Via
Udacity
Instructors
Sebastian Thrun
Cezanne Camacho
Jay Alammar
Alexis Cook
Luis Serrano
Juan Delgado
Ortal Arel
Language
English
Good to know
Suitable for students pursuing a career in artificial intelligence or machine learning
Covers a range of foundational concepts in natural language processing
Led by instructors who are recognized for their contributions to the field
Emphasizes hands-on learning through practical exercises and projects
Suitable for both beginners and those looking to strengthen their foundation in natural language processing
May require students to have some prior knowledge in Python programming
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