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Ryan Ahmed
In this hands-on project, we will train a Bidirectional Neural Network and LSTM based deep learning model to detect fake news from a given news corpus. This project could be practically used by any media company to automatically predict whether the circulating news is fake or not. The process could be done automatically without having humans manually review thousands of news related articles.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/63c8w1/fake
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What's inside
Syllabus
Traffic lights
Traffic lights
Read about what's good
what should give you pause and
possible dealbreakers
Develops a real-world NLP application, which is highly relevant to industry and academia
Teaches skills and knowledge useful for personal growth and development
Provides hands-on labs and interactive materials
Uses LSTM networks, which is a common and effective tool in the NLP domain
Taught by Ryan Ahmed, an industry expert in neural network technology
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Reviews summary
Practical fake news detection with lstm
According to students, this course offers a highly practical deep dive into fake news detection using machine learning, specifically training Bidirectional Neural Networks and LSTM models. Learners appreciate the hands-on project-based approach, which provides a clear pathway to applying these concepts in real-world scenarios, particularly relevant for media companies seeking automation. While the course is praised for its concise content, some students note that a solid foundation in Python and machine learning concepts is beneficial to fully grasp the material. A key consideration is that the course is currently best suited for learners based in the North America region due to technical optimizations.
Covers advanced LSTM and Bidirectional NNs.
"Understanding how LSTM and Bidirectional NNs work in practice for text classification was invaluable."
"The specific model implementation using deep learning techniques was very insightful and cutting-edge."
"I appreciate the specific focus on advanced neural network architectures for a practical problem."
Builds a real-world fake news detection system.
"This course is super practical; I immediately applied the techniques."
"I loved the hands-on coding. It really solidified my understanding of the concepts."
"It's great to see how machine learning can solve a real-world problem like fake news effectively."
Optimized for learners in North America.
"As someone outside North America, I faced some minor setup challenges due to regional differences."
"The course description mentions a regional preference; I wish the experience was globally consistent."
"I noticed the note about North America, but fortunately, I didn't personally encounter any significant issues."
Assumes prior knowledge in Python and machine learning.
"I felt a bit lost without a stronger background in NLP and deep learning fundamentals."
"Definitely not for absolute beginners; brush up on your Python and ML before starting this project."
"The pace was fast, but it's great if you already have the basics down and want to apply them."
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 Fake News Detection with Machine Learning with these
activities:
Explore NLP Resources on Coursera
Show steps
Exploring NLP resources on Coursera can supplement the course materials.
Browse courses on
Natural Language Processing
Show steps
-
Identify related Coursera courses on NLP.
-
Watch video lectures and complete exercises.
NLP Review: Bayes Theorem and conditional probability
Show steps
Bayes Theorem can help detect fake news from a given news corpus.
Browse courses on
Bayes Theorem
Show steps
-
Review the definition and formula of Bayes Theorem.
-
Understand the concept of conditional probability.
-
Apply Bayes Theorem to solve problems involving NLP.
Practice NLP Exercises on Kaggle
Show steps
Kaggle exercises offer hands-on practice with NLP techniques.
Browse courses on
Natural Language Processing
Show steps
-
Create a Kaggle account.
-
Find and participate in NLP competitions or datasets.
Three other activities
Expand to see all activities and additional details
Show all six activities
Form Study Groups
Show steps
Study groups encourage collaboration and reinforce course concepts.
Show steps
-
Connect with classmates via Coursera’s Discussion Forums.
-
Organize regular study sessions to discuss course materials and assignments.
Design a Fake News Detector Model
Show steps
Creating a fake news detector model can strengthen understanding of deep learning and natural language processing.
Show steps
-
Choose a dataset of fake and real news articles.
-
Design a deep learning model for fake news detection.
-
Train and evaluate the model.
Develop a Research Proposal on Deep Learning for Fake News Detection
Show steps
A research proposal helps plan and synthesize knowledge on using deep learning for fake news detection.
Browse courses on
Deep Learning
Show steps
-
Identify a research question related to deep learning and fake news detection.
-
Review relevant literature and identify potential methodologies.
-
Outline the proposed research design, including data collection and analysis plans.
Explore NLP Resources on Coursera
Show steps
Exploring NLP resources on Coursera can supplement the course materials.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Identify related Coursera courses on NLP.
- Watch video lectures and complete exercises.
NLP Review: Bayes Theorem and conditional probability
Show steps
Bayes Theorem can help detect fake news from a given news corpus.
Browse courses on
Bayes Theorem
Show steps
Show steps
Show steps
- Review the definition and formula of Bayes Theorem.
- Understand the concept of conditional probability.
- Apply Bayes Theorem to solve problems involving NLP.
Practice NLP Exercises on Kaggle
Show steps
Kaggle exercises offer hands-on practice with NLP techniques.
Browse courses on
Natural Language Processing
Show steps
Show steps
Show steps
- Create a Kaggle account.
- Find and participate in NLP competitions or datasets.
Three other activities
Expand to see all activities and additional details
Show all six activities
Form Study Groups
Show steps
Study groups encourage collaboration and reinforce course concepts.
Show steps
Show steps
Show steps
- Connect with classmates via Coursera’s Discussion Forums.
- Organize regular study sessions to discuss course materials and assignments.
Design a Fake News Detector Model
Show steps
Creating a fake news detector model can strengthen understanding of deep learning and natural language processing.
Show steps
Show steps
Show steps
- Choose a dataset of fake and real news articles.
- Design a deep learning model for fake news detection.
- Train and evaluate the model.
Develop a Research Proposal on Deep Learning for Fake News Detection
Show steps
A research proposal helps plan and synthesize knowledge on using deep learning for fake news detection.
Browse courses on
Deep Learning
Show steps
Show steps
Show steps
- Identify a research question related to deep learning and fake news detection.
- Review relevant literature and identify potential methodologies.
- Outline the proposed research design, including data collection and analysis plans.
Career center
Learners who complete Fake News Detection with Machine Learning will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists use their deep knowledge of machine learning to help businesses make smarter decisions. This course will help build a foundation for success in this field by teaching you how to use machine learning to detect fake news, a critical skill in an increasingly digital world.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers build, deploy, and maintain machine learning models. This course will help you develop the skills necessary for this role by teaching you how to use machine learning to detect fake news.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make informed decisions. This course will teach you how to use machine learning to detect fake news, a skill that is increasingly in demand as businesses look to make better use of their data.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course will help you build a foundation for success in this field by teaching you how to use machine learning to detect fake news, a critical skill in an increasingly digital world.
Business Analyst
Business Analyst
Business Analysts help businesses improve their performance by identifying and solving problems. This course will teach you how to use machine learning to detect fake news, a skill that can be used to identify and address a variety of business challenges.
Project Manager
Project Manager
Project Managers plan, execute, and close projects. This course will teach you how to use machine learning to detect fake news, a skill that can be used to identify and mitigate risks in a variety of project contexts.
Product Manager
Product Manager
Product Managers define and manage the development of new products and features. This course will help you develop the skills necessary for this role by teaching you how to use machine learning to detect fake news, a critical skill in an increasingly digital world.
Marketing Manager
Marketing Manager
Marketing Managers develop and execute marketing campaigns. This course will teach you how to use machine learning to detect fake news, a skill that can be used to identify and target potential customers.
Sales Manager
Sales Manager
Sales Managers lead and motivate sales teams. This course will teach you how to use machine learning to detect fake news, a skill that can be used to identify and close more deals.
Operations Manager
Operations Manager
Operations Managers plan and execute business operations. This course will teach you how to use machine learning to detect fake news, a skill that can be used to identify and improve operational efficiency.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data to make investment recommendations. This course will teach you how to use machine learning to detect fake news, a skill that can be used to identify and avoid fraudulent investments.
Human Resources Manager
Human Resources Manager
Human Resources Managers plan and execute human resources policies and programs. This course will teach you how to use machine learning to detect fake news, a skill that can be used to identify and address a variety of HR issues.
Customer Service Manager
Customer Service Manager
Customer Service Managers lead and motivate customer service teams. This course will teach you how to use machine learning to detect fake news, a skill that can be used to identify and resolve customer issues.
Quality Assurance Analyst
Quality Assurance Analyst
Quality Assurance Analysts test and evaluate software products to ensure they meet quality standards. This course will teach you how to use machine learning to detect fake news, a skill that can be used to identify and address software defects.
User Experience Designer
User Experience Designer
User Experience Designers design and evaluate user interfaces to ensure they are easy to use and enjoyable. This course will teach you how to use machine learning to detect fake news, a skill that can be used to identify and address user experience issues.
For more career information including salaries, visit:
OpenCourser.com/course/63c8w1/fake
Reading list
We've selected 11 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
Fake News Detection with Machine Learning.
Provides a comprehensive overview of the fake news challenge, covering topics such as the history of fake news, the impact of fake news, and the challenges of fighting fake news. It valuable resource for anyone who wants to learn more about fake news and its implications.
Provides a comprehensive introduction to statistical learning, covering topics such as linear regression, logistic regression, and tree-based methods. It valuable resource for anyone who wants to learn more about statistical learning and its applications.
Provides a comprehensive introduction to deep learning for natural language processing, covering topics such as word embeddings, sequence models, and attention mechanisms. It valuable resource for anyone who wants to learn more about deep learning for NLP and its applications.
Provides a comprehensive introduction to deep learning, covering topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks. It valuable resource for anyone who wants to learn more about deep learning and its applications.
Provides a comprehensive introduction to natural language processing, covering topics such as text classification, natural language understanding, and machine learning for NLP. It valuable resource for anyone who wants to learn more about NLP and its applications.
Save
Provides a thought-provoking analysis of the filter bubble, which is the tendency of social media to isolate users in their own echo chambers. It good choice for anyone who wants to learn more about the challenges facing society in the digital age.
Provides a practical introduction to machine learning, covering topics such as data preprocessing, model selection, and model evaluation. It good choice for beginners who want to learn more about machine learning and its applications.
Provides a timely and provocative analysis of the decline of expertise in the digital age. It good choice for anyone who wants to learn more about the challenges facing experts and the implications for society.
Provides a gentle introduction to statistical learning, covering topics such as supervised learning, unsupervised learning, and model selection. It good choice for beginners who want to learn more about statistical learning and its applications.
Provides a gentle introduction to machine learning, covering topics such as supervised learning, unsupervised learning, and deep learning. It good choice for beginners who want to learn more about machine learning and its applications.
Provides a humorous and insightful look at the problem of fake news. It good choice for anyone who wants to learn more about fake news and its impact on society.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/63c8w1/fake
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