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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.
Read more
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.
Read more
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
NLP Fake News Detector
In this hands-on project, we will train a Long Short Term Memory (LSTM) network to detect fake news from a given news corpus. This project could be practically used by media companies 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.
Good to know
Good to know
Know what's good ,
what to watch for , 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
Save this course
Save Fake News Detection with Machine Learning to your list so you can find it easily later:
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Reviews summary
Fake news detection with ml projects
Learners say that this is a great course for beginners interested in learning about fake news detection using Python and machine learning. Those new to Python should be cautious and may want to consider taking an introductory course first. The course includes in-depth but accessible lectures, clear code explanations, and hands-on projects. Overall, this course is well received by learners and many find it to be an informative and engaging experience.
Instructor provides clear explanations
"Instructor Ryan has taken a lot of efforts to explain the topics, Advanced concepts like RNNs and LSTMs are clearly explained."
"Thank you so much sir for creating the course."
"really enjoyed your insights and the explanations were very crisp and clear."
"The instructor goes through the code, which is explained well."
Combines theoretical foundations with practical application
"This project is very comprehensive and easy to follow."
"It expertly blends theoretical foundations with hands-on practicality, enabling both beginners and experienced learners to grasp the intricacies of fake news detection using machine learning."
"This project has a succint but very good theoretic explanation, combined with a very thorough practical application"
Projects are worthwhile and informative
"Great practice for important concepts in data science."
"Amazing Course ! Expand my knowledge about NLP"
"Really fun project with amazing instructor."
"Very useful project, the instructor is very clear in presenting information"
Training models can take a long time
"Compute time for model training is very long if using external Jupyter Notebook to follow along."
Intended for beginners, prior programming knowledge can be helpful
"Not that good for people new to python and ml, many high level concepts are used in this project!"
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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Effort
2 hours
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Ryan Ahmed
Language
English
Good to know
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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