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Charles Ivan Niswander II
"Fake News" is a word used to mean different things to different people. At its heart, we define "fake news" as any news stories which are false: the article itself is fabricated without verifiable evidence, citations or quotations. Often these stories may be...
Read more
"Fake News" is a word used to mean different things to different people. At its heart, we define "fake news" as any news stories which are false: the article itself is fabricated without verifiable evidence, citations or quotations. Often these stories may be...
Read more
"Fake News" is a word used to mean different things to different people. At its heart, we define "fake news" as any news stories which are false: the article itself is fabricated without verifiable evidence, citations or quotations. Often these stories may be lies and propaganda that is deliberately intended to confuse the viewer, or may be characterized as "click-bait" written for monetary incentives (the writer profits on the number of people who click on the story). In recent years, fake news stories have proliferated via social media, partially because they are so readily and widely spread online. Worse yet, Artificial Intelligence and natural language processing, or NLP, technology is ushering in an era of artificially-generated fake news. Both types of fake news are detectable with the use of NLP and deep learning.
In this project, you will learn multiple computational methods of identifying and classifying Fake News.
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/jx5nn7/detect
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Reviews summary
Challenging but interesting
This course on detecting fake news in Python with Tensorflow receives mixed reviews from learners. While one learner found the topic interesting and the instruction good, another learner experienced difficulties following along due to the lack of a Jupyter Notebook environment and unclear video instruction. The learner who experienced difficulties ended up running out of time and spent more time debugging their code than learning.
Good instruction.
"Interesting topic! Good instruction."
Interesting topic.
"Interesting topic! Good instruction."
Unclear video instruction.
"Also, in one of the videos, the instructor neglects to point out a lot of miscellaneous edits made to the code (he obviously cut out a few portions from the video where he made edits), so it became very confusing as I was trying to compare my code to his in order to debug."
Should have been done in Jupyter Notebook.
"This was very hard to follow along, not necessarily because of the difficulty level of the content. Because this wasn't done in a Jupyter Notebook, I wouldn't realize that I had an error anywhere in my code until I ran the whole file."
Spent more time debugging than learning.
"I ended up spending way more time trying to debug my code rather than trying to understand what my code was doing."
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 Detect Fake News in Python with Tensorflow with these
activities:
Read 'Natural Language Processing with PyTorch'
Show steps
Expand your theoretical knowledge of NLP and PyTorch.
View
Natural Language Processing with PyTorch: Build...
on Amazon
Show steps
-
Read the book paying attention to topics relevant to the course.
-
Summarize the key concepts and ideas from the book.
Connect with NLP Experts
Show steps
Identify NLP professionals who can provide guidance and support throughout your learning journey.
Show steps
-
Attend industry events or conferences.
-
Reach out to NLP experts on LinkedIn.
-
Join online NLP communities and forums.
Review Natural Language Processing Algorithms
Show steps
Start the course with foundational skills by reviewing key NLP algorithms and concepts.
Show steps
-
Identify the NLP algorithms that will be covered in this course.
-
Review the mathematics behind these algorithms.
-
Try implementing some of these algorithms in the programming language of your choice.
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Follow NLP Tutorials
Show steps
Supplement the course material with additional tutorials on NLP techniques.
Show steps
-
Identify reliable sources for NLP tutorials.
-
Choose tutorials that align with the topics covered in the course.
-
Follow the tutorials step-by-step to enhance your understanding.
Follow tutorials on natural language processing
Show steps
Expand your knowledge of NLP and improve your skills in detecting fake news.
Browse courses on
NLP
Show steps
-
Find a tutorial on natural language processing
-
Follow the tutorial and complete the exercises
-
Apply what you have learned to the analysis of fake news
Solve NLP Kaggle Challenges
Show steps
Gain real-world experience by attempting to solve challenges related to NLP.
Show steps
-
Develop a solution using NLP techniques.
-
Submit your solution and analyze the results.
-
Find a relevant Kaggle challenge.
-
Review the problem statement and understand the data.
Analyze news articles
Show steps
Get hands-on practice analyzing news articles to improve your ability to identify fake news.
Browse courses on
NLP
Show steps
-
Select a news article that you are interested in
-
Read the article carefully and take notes on the main points
-
Analyze the article's structure, language, and tone
-
Identify any red flags that may indicate that the article is fake news
-
Write a brief summary of your findings
Sentiment Analysis of Movie Reviews
Show steps
Apply your NLP skills to a practical project that can reinforce concepts from the course.
Show steps
-
Gather a dataset of movie reviews.
-
Preprocess the reviews to remove noise and unnecessary words.
-
Decide on relevant feature set for training a NLP model to perform sentiment analysis.
-
Train and evaluate a sentiment analysis model.
-
Use the model to analyze new movie reviews and determine their sentiment.
Create a fake news detection toolkit
Show steps
Build a collection of resources that can help you identify and classify fake news.
Browse courses on
NLP
Show steps
-
Gather a list of resources on fake news detection
-
Organize the resources into a toolkit
-
Share the toolkit with others
Contribute to Open-Source NLP Projects
Show steps
Deepen your understanding of NLP by contributing to a community project.
Show steps
-
Identify open-source NLP projects on GitHub.
-
Review the documentation and find areas where you can contribute.
-
Submit a pull request with your changes.
Build a Fake News Detector
Show steps
Challenge yourself to apply all the concepts from the course. Build a tool to detect fake news!
Show steps
-
Gather data on fake and real news.
-
Identify features that can help distinguish fake news from real news.
-
Develop a model to detect fake news using NLP techniques.
-
Evaluate the accuracy of your model.
-
Package your solution and write a brief report.
Help Others on NLP Forums
Show steps
Support the NLP community while reinforcing your understanding of concepts.
Show steps
-
Find NLP forums or communities.
-
Answer questions and provide support to other learners.
-
Engage in discussions and share your knowledge.
Read 'Natural Language Processing with PyTorch'
Show steps
Expand your theoretical knowledge of NLP and PyTorch.
View
Natural Language Processing with PyTorch: Build...
on Amazon
Show steps
Show steps
Show steps
- Read the book paying attention to topics relevant to the course.
- Summarize the key concepts and ideas from the book.
Connect with NLP Experts
Show steps
Identify NLP professionals who can provide guidance and support throughout your learning journey.
Show steps
Show steps
Show steps
- Attend industry events or conferences.
- Reach out to NLP experts on LinkedIn.
- Join online NLP communities and forums.
Review Natural Language Processing Algorithms
Show steps
Start the course with foundational skills by reviewing key NLP algorithms and concepts.
Show steps
Show steps
Show steps
- Identify the NLP algorithms that will be covered in this course.
- Review the mathematics behind these algorithms.
- Try implementing some of these algorithms in the programming language of your choice.
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Follow NLP Tutorials
Show steps
Supplement the course material with additional tutorials on NLP techniques.
Show steps
Show steps
Show steps
- Identify reliable sources for NLP tutorials.
- Choose tutorials that align with the topics covered in the course.
- Follow the tutorials step-by-step to enhance your understanding.
Follow tutorials on natural language processing
Show steps
Expand your knowledge of NLP and improve your skills in detecting fake news.
Browse courses on
NLP
Show steps
Show steps
Show steps
- Find a tutorial on natural language processing
- Follow the tutorial and complete the exercises
- Apply what you have learned to the analysis of fake news
Solve NLP Kaggle Challenges
Show steps
Gain real-world experience by attempting to solve challenges related to NLP.
Show steps
Show steps
Show steps
- Develop a solution using NLP techniques.
- Submit your solution and analyze the results.
- Find a relevant Kaggle challenge.
- Review the problem statement and understand the data.
Analyze news articles
Show steps
Get hands-on practice analyzing news articles to improve your ability to identify fake news.
Browse courses on
NLP
Show steps
Show steps
Show steps
- Select a news article that you are interested in
- Read the article carefully and take notes on the main points
- Analyze the article's structure, language, and tone
- Identify any red flags that may indicate that the article is fake news
- Write a brief summary of your findings
Sentiment Analysis of Movie Reviews
Show steps
Apply your NLP skills to a practical project that can reinforce concepts from the course.
Show steps
Show steps
Show steps
- Gather a dataset of movie reviews.
- Preprocess the reviews to remove noise and unnecessary words.
- Decide on relevant feature set for training a NLP model to perform sentiment analysis.
- Train and evaluate a sentiment analysis model.
- Use the model to analyze new movie reviews and determine their sentiment.
Create a fake news detection toolkit
Show steps
Build a collection of resources that can help you identify and classify fake news.
Browse courses on
NLP
Show steps
Show steps
Show steps
- Gather a list of resources on fake news detection
- Organize the resources into a toolkit
- Share the toolkit with others
Contribute to Open-Source NLP Projects
Show steps
Deepen your understanding of NLP by contributing to a community project.
Show steps
Show steps
Show steps
- Identify open-source NLP projects on GitHub.
- Review the documentation and find areas where you can contribute.
- Submit a pull request with your changes.
Build a Fake News Detector
Show steps
Challenge yourself to apply all the concepts from the course. Build a tool to detect fake news!
Show steps
Show steps
Show steps
- Gather data on fake and real news.
- Identify features that can help distinguish fake news from real news.
- Develop a model to detect fake news using NLP techniques.
- Evaluate the accuracy of your model.
- Package your solution and write a brief report.
Help Others on NLP Forums
Show steps
Support the NLP community while reinforcing your understanding of concepts.
Show steps
Show steps
Show steps
- Find NLP forums or communities.
- Answer questions and provide support to other learners.
- Engage in discussions and share your knowledge.
Career center
Learners who complete Detect Fake News in Python with Tensorflow will develop knowledge and skills
that may be useful to these careers:
Natural Language Processing Engineer
Natural Language Processing Engineer
A Natural Language Processing Engineer designs, develops, and maintains Natural Language Processing systems. As this course's focus is on Natural Language Processing and Fake News detection, it would provide a deep dive into the exact technologies Natural Language Processing Engineers work with. This course would be useful for any Natural Language Processing Engineer, and especially those interested in Fake News detection.
Information Security Analyst
Information Security Analyst
An Information Security Analyst protects an organization's computer systems and networks from unauthorized access, use, disclosure, disruption, modification, or destruction. This course dives into Fake News detection, which has become an increasingly relevant topic for Information Security Analysts as fake news can be used to spread malware, phishing attacks, and ransomware. This course is highly relevant for Information Security Analysts.
Computational Linguist
Computational Linguist
A Computational Linguist combines computer science and linguistics to analyze and understand human language. Natural Language Processing, a major topic of this course, is critical for Computational Linguists when performing their work. This course may be useful for current Computational Linguists, as well as for those interested in getting started in the field.
Cybersecurity Analyst
Cybersecurity Analyst
A Cybersecurity Analyst protects an organization’s computer systems and networks from unauthorized access, use, disclosure, disruption, modification, or destruction. This course will help Cybersecurity Analysts understand how to detect Fake News, which can be used to spread malware, phishing attacks, and ransomware. This course would be especially useful for Cybersecurity Analysts who work with threat intelligence.
Fraud Analyst
Fraud Analyst
A Fraud Analyst investigates and prevents fraud. This course covers Fake News detection, which has become increasingly sophisticated and can be used to facilitate fraud. Fraud Analysts may find this course useful, as it can help them stay up-to-date on the latest Fake News detection techniques.
Media Analyst
Media Analyst
A Media Analyst analyzes media content to identify trends and patterns. This course will help Media Analysts understand how to detect Fake News, which is an increasingly important skill in the digital age. This course would be especially useful for Media Analysts who work with social media analysis.
Journalist
Journalist
A Journalist researches, writes, and reports on news and current events. This course will help Journalists understand how to detect Fake News, which is an increasingly important skill in the digital age. This course would be especially useful for Journalists who cover politics or social issues.
Digital Marketing Specialist
Digital Marketing Specialist
A Digital Marketing Specialist plans and executes marketing campaigns across digital channels such as search engines, social media, email, and websites. This course will help Digital Marketing Specialists understand how to detect Fake News, which can be damaging to brands and organizations. This course would be especially useful for Digital Marketing Specialists who work with social media marketing.
Public Relations Specialist
Public Relations Specialist
A Public Relations Specialist manages and disseminates information between an organization and its key publics. This course will help Public Relations Specialists understand how to detect Fake News, which can damage an organization’s reputation. This course would be especially useful for Public Relations Specialists who work with media relations.
Law Enforcement Officer
Law Enforcement Officer
A Law Enforcement Officer enforces the law and protects the public. This course will help Law Enforcement Officers understand how to detect Fake News, which can be used to spread misinformation and incite violence. This course would be especially useful for Law Enforcement Officers who work with community policing or homeland security.
Data Analyst
Data Analyst
A Data Analyst collects, analyzes, interprets, and presents data to help organizations make better decisions. This course on Fake News detection uses Natural Language Processing and deep learning, two techniques often employed by Data Analysts when parsing through data for insights. By taking this course, you will build a strong foundation in the technologies Data Analysts utilize.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer designs, develops, and maintains machine learning systems. Like Artificial Intelligence Engineers, Machine Learning Engineers often utilize Natural Language Processing and deep learning when building their systems. This course provides a foundation in both topics, making it a good starting point for those interested in Machine Learning Engineering.
Data Scientist
Data Scientist
A Data Scientist uses data to build models, which can be used to understand patterns and make predictions. In this Techonology Intelligence course, you will learn about Natural Language Processing and Artificial Intelligence. Both are key components of helping Data Scientists create quality models. This course may be useful in understanding the building blocks of Data Science, as well as providing a good foundation for some of the tools Data Scientists utilize.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
An Artificial Intelligence Engineer designs, develops, and maintains AI systems. This Fake News detection course dives into Artificial Intelligence techniques such as Natural Language Processing and deep learning. These technologies form the backbone of many of the AI systems that Artificial Intelligence Engineers build, so this course may be useful in getting started in the field.
Software Engineer
Software Engineer
A Software Engineer designs, develops, and maintains software systems. While the focus is typically not on utilizing Artificial Intelligence or Natural Language Processing, this course may be useful for Software Engineers who want to add these technologies to their skillset.
For more career information including salaries, visit:
OpenCourser.com/course/jx5nn7/detect
Reading list
We've selected eight 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
Detect Fake News in Python with Tensorflow .
Provides a comprehensive overview of deep learning, covering topics such as convolutional neural networks, recurrent neural networks, and generative adversarial networks. It valuable resource for anyone interested in learning more about the field.
Provides a comprehensive overview of natural language processing, covering topics such as text classification, part-of-speech tagging, and named entity recognition. It valuable resource for anyone interested in learning more about the field.
Provides a comprehensive overview of the fourth industrial revolution, covering topics such as the history of the industrial revolution, the impact of the industrial revolution, and the ways to control the industrial revolution. It valuable resource for anyone interested in learning more about the field.
Provides a comprehensive overview of machine learning, covering topics such as supervised learning, unsupervised learning, and deep learning. It valuable resource for anyone interested in learning more about the field.
Save
Provides a comprehensive overview of the age of information, covering topics such as the history of AI, the impact of AI, and the ways to control AI. It valuable resource for anyone interested in learning more about the field.
Save
Provides a comprehensive overview of data science, covering topics such as data collection, data analysis, and data visualization. It valuable resource for anyone interested in learning more about the field.
Save
Provides a comprehensive overview of data visualization, covering topics such as data visualization techniques, data visualization tools, and data visualization best practices. It valuable resource for anyone interested in learning more about the field.
Provides a comprehensive overview of data mining, covering topics such as data mining techniques, data mining tools, and data mining best practices. It valuable resource for anyone interested in learning more about the field.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/jx5nn7/detect
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Charles Ivan Niswander II
Good to know
Sharpens pre-existing expertise for learners who have already established a strong foundation
Involves use of a variety of media to deliver material, including videos and discussions
May be especially valuable for students seeking to understand topics in innovation
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