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Emmanuel Acheampong
Welcome to the “Deploy an NLP Text Generator: Bart Simpson Chalkboard Gag” guided project.
Read more
Welcome to the “Deploy an NLP Text Generator: Bart Simpson Chalkboard Gag” guided project.
Read more
Welcome to the “Deploy an NLP Text Generator: Bart Simpson Chalkboard Gag” guided project.
Text Generation is a natural language technique that leverages language modeling to create or predict new text based on texts it has been trained on. An example of text generation can be identified in the Gmail sentence autocomplete feature.
In this project, we will deploy an NLP text generator model as a python Streamlit app. The model, which has been trained on all the text from Bart Simpsons chalkboard gag from the Simpsons, will be able to autogenerate new chalkboard gags.
This project is an intermediate python project for anyone interested in learning about how to productionize natural language text generator models as a Streamlit app on Heroku. It requires preliminary knowledge on how to build and train NLP text generator models (as we will not be building or training models) and how to utilize Git. Learners would also need a Heroku account and some familiarity with the Python Streamlit module.
At the end of this project, learners will have a publicly available Streamlit web app that leverages natural language processing text generation to generate new text for Bart Simpsons' chalkboard gags.
Register for this course and see more details by visiting:
OpenCourser.com/course/zm5wbb/deploy
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Syllabus
Project Overview
Welcome to the “Deploy an NLP Text Generator: Bart Simpson Chalkboard Gag” guided project.
Text Generation is a natural language technique that leverages language modeling to create or predict new text based on texts it has been trained on. An example of text generation can be identified in the Gmail sentence autocomplete feature.
In this project, we will deploy an NLP text generator model as a python Streamlit app. The model, which has been trained on all the text from Bart Simpsons chalkboard gag from the Simpsons, will be able to autogenerate new chalkboard gags.
This project is an intermediate python project for anyone interested in learning about how to productionize natural language text generator models as a Streamlit app on Heroku. It requires preliminary knowledge on how to build and train NLP text generator models (as we will not be building or training models) and how to utilize Git. Learners would also need a Heroku account and some familiarity with the Python Streamlit module.
At the end of this project, learners will have a publicly available Streamlit web app that leverages natural language processing text generation to generate new text for Bart Simpsons' chalkboard gags.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Fits audience with background in natural language processing
Introduces techniques in natural language processing
Practical application of text generation with Python
Requires familiarity with Git
Requires a Heroku account
Assumes knowledge of Python Streamlit module
Save this course
Save Deploy an NLP Text Generator: Bart Simpson Chalkboard Gag to your list so you can find it easily later:
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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 Deploy an NLP Text Generator: Bart Simpson Chalkboard Gag with these
activities:
Seek guidance from a mentor in text generation
Show steps
Connect with experienced professionals in text generation to gain valuable insights and guidance throughout your learning journey.
Show steps
-
Identify potential mentors through professional networks or online platforms
-
Reach out to mentors and express your interest in their guidance
-
Schedule regular meetings or calls
-
Seek feedback and advice on your projects and career goals
-
Maintain a mutually beneficial relationship with your mentor
Review 'Natural Language Processing with Python'
Show steps
Supplement your understanding of text generation by reading a book dedicated to natural language processing with Python.
View
Natural Language Processing with Python:...
on Amazon
Show steps
-
Obtain a copy of the book
-
Read the book thoroughly
-
Take notes and highlight important concepts
-
Complete the exercises and projects in the book
-
Discuss the book with other learners
Compile a list of resources on text generation
Show steps
Gather and organize resources on text generation, such as tutorials, articles, and books, to supplement your learning.
Show steps
-
Search for resources on text generation
-
Evaluate the relevance and quality of resources
-
Organize resources into a list
-
Share the list with other learners
Five other activities
Expand to see all activities and additional details
Show all eight activities
Participate in a peer study group
Show steps
Collaborate with other learners to discuss the concepts of text generation and troubleshoot any challenges you may encounter.
Show steps
-
Find a study partner or group
-
Set regular meeting times
-
Discuss course materials
-
Work on projects together
-
Provide feedback and support to each other
Generate chalkboard gags
Show steps
Practice generating new chalkboard gags using the deployed model to improve your understanding of text generation.
Show steps
-
Open the deployed web app
-
Enter a prefix for the chalkboard gag
-
Click the 'Generate' button
-
Review the generated chalkboard gag
-
Repeat steps 2-4 with different prefixes
Explore additional tutorials on text generation
Show steps
Seek out and follow tutorials on text generation to enhance your understanding and skills.
Show steps
-
Search for tutorials on text generation
-
Select tutorials that are relevant to your level of knowledge
-
Follow the tutorials step-by-step
-
Apply what you learn to your own projects
-
Share your findings with other learners
Create a blog post
Show steps
Write a blog post that explains the concepts behind text generation and the process of deploying an NLP model as a web app.
Show steps
-
Research text generation and Streamlit
-
Develop an outline for your blog post
-
Write the content for your blog post
-
Edit and proofread your blog post
-
Publish your blog post
Contribute to an open-source project on text generation
Show steps
Apply your skills in text generation by contributing to an open-source project, gaining practical experience and making a valuable contribution to the community.
Show steps
-
Identify open-source projects related to text generation
-
Review the project documentation and codebase
-
Identify areas where you can contribute
-
Submit pull requests with your contributions
-
Collaborate with other contributors
Seek guidance from a mentor in text generation
Show steps
Connect with experienced professionals in text generation to gain valuable insights and guidance throughout your learning journey.
Show steps
Show steps
Show steps
- Identify potential mentors through professional networks or online platforms
- Reach out to mentors and express your interest in their guidance
- Schedule regular meetings or calls
- Seek feedback and advice on your projects and career goals
- Maintain a mutually beneficial relationship with your mentor
Review 'Natural Language Processing with Python'
Show steps
Supplement your understanding of text generation by reading a book dedicated to natural language processing with Python.
View
Natural Language Processing with Python:...
on Amazon
Show steps
Show steps
Show steps
- Obtain a copy of the book
- Read the book thoroughly
- Take notes and highlight important concepts
- Complete the exercises and projects in the book
- Discuss the book with other learners
Compile a list of resources on text generation
Show steps
Gather and organize resources on text generation, such as tutorials, articles, and books, to supplement your learning.
Show steps
Show steps
Show steps
- Search for resources on text generation
- Evaluate the relevance and quality of resources
- Organize resources into a list
- Share the list with other learners
Five other activities
Expand to see all activities and additional details
Show all eight activities
Participate in a peer study group
Show steps
Collaborate with other learners to discuss the concepts of text generation and troubleshoot any challenges you may encounter.
Show steps
Show steps
Show steps
- Find a study partner or group
- Set regular meeting times
- Discuss course materials
- Work on projects together
- Provide feedback and support to each other
Generate chalkboard gags
Show steps
Practice generating new chalkboard gags using the deployed model to improve your understanding of text generation.
Show steps
Show steps
Show steps
- Open the deployed web app
- Enter a prefix for the chalkboard gag
- Click the 'Generate' button
- Review the generated chalkboard gag
- Repeat steps 2-4 with different prefixes
Explore additional tutorials on text generation
Show steps
Seek out and follow tutorials on text generation to enhance your understanding and skills.
Show steps
Show steps
Show steps
- Search for tutorials on text generation
- Select tutorials that are relevant to your level of knowledge
- Follow the tutorials step-by-step
- Apply what you learn to your own projects
- Share your findings with other learners
Create a blog post
Show steps
Write a blog post that explains the concepts behind text generation and the process of deploying an NLP model as a web app.
Show steps
Show steps
Show steps
- Research text generation and Streamlit
- Develop an outline for your blog post
- Write the content for your blog post
- Edit and proofread your blog post
- Publish your blog post
Contribute to an open-source project on text generation
Show steps
Apply your skills in text generation by contributing to an open-source project, gaining practical experience and making a valuable contribution to the community.
Show steps
Show steps
Show steps
- Identify open-source projects related to text generation
- Review the project documentation and codebase
- Identify areas where you can contribute
- Submit pull requests with your contributions
- Collaborate with other contributors
Career center
Learners who complete Deploy an NLP Text Generator: Bart Simpson Chalkboard Gag will develop knowledge and skills
that may be useful to these careers:
Natural Language Processing Engineer
Natural Language Processing Engineer
Natural Language Processing Engineers are responsible for developing and deploying natural language processing models. They must know how to use a variety of natural language processing techniques, including text generation. A course in NLP text generation can help you build the skills you need to succeed as a Natural Language Processing Engineer. In particular, this course teaches you how to build a natural language text generator model and deploy it as a Streamlit app. This skill can be useful for a variety of tasks, such as developing chatbots, writing marketing copy, and generating product descriptions.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for developing and deploying machine learning models. They must know how to use a variety of machine learning techniques, including natural language processing. A course in NLP text generation can help you build the skills you need to succeed as a Machine Learning Engineer. In particular, this course teaches you how to build a natural language text generator model and deploy it as a Streamlit app. This skill can be useful for a variety of tasks, such as developing chatbots, writing marketing copy, and generating product descriptions.
Data Scientist
Data Scientist
Data Scientists play an important role in many different industries. They use data to develop models, predict trends, and make decisions. Data Scientists must know how to use programming languages, interpret data, and communicate their findings. A course in NLP text generation can help you build the skills you need to succeed as a Data Scientist. In particular, this course teaches you how to use a natural language text generator model to create or predict new text. This skill can be useful for a variety of tasks, such as developing chatbots, writing marketing copy, and generating product descriptions.
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, analyzing, and interpreting data. They must know how to use a variety of data analysis tools and techniques. A course in NLP text generation can help you build the skills you need to succeed as a Data Analyst. In particular, this course teaches you how to use a natural language text generator model to create or predict new text. This skill can be useful for a variety of tasks, such as identifying trends, predicting customer behavior, and developing marketing campaigns.
Software Engineer
Software Engineer
Software Engineers are responsible for developing and maintaining software applications. They must know how to use a variety of programming languages and software development tools. A course in NLP text generation can help you build the skills you need to succeed as a Software Engineer. In particular, this course teaches you how to use a natural language text generator model to create or predict new text. This skill can be useful for a variety of tasks, such as developing chatbots, writing marketing copy, and generating product descriptions.
Business Analyst
Business Analyst
Business Analysts are responsible for analyzing business processes and developing solutions to improve efficiency. They must know how to use a variety of business analysis tools and techniques. A course in NLP text generation can help you build the skills you need to succeed as a Business Analyst. In particular, this course teaches you how to use a natural language text generator model to create or predict new text. This skill can be useful for a variety of tasks, such as writing business requirements, developing process maps, and creating presentation materials.
Marketing Manager
Marketing Manager
Marketing Managers are responsible for developing and implementing marketing campaigns. They must know how to understand customer needs, develop marketing strategies, and manage marketing budgets. A course in NLP text generation can help you build the skills you need to succeed as a Marketing Manager. In particular, this course teaches you how to use a natural language text generator model to create or predict new text. This skill can be useful for a variety of tasks, such as writing marketing copy, developing email campaigns, and creating social media content.
Human Resources Manager
Human Resources Manager
Human Resources Managers are responsible for managing the human resources of an organization. They must know how to recruit, hire, train, and develop employees. A course in NLP text generation can help you build the skills you need to succeed as a Human Resources Manager. In particular, this course teaches you how to use a natural language text generator model to create or predict new text. This skill can be useful for a variety of tasks, such as writing job descriptions, developing employee training programs, and creating performance evaluations.
Financial Analyst
Financial Analyst
Financial Analysts are responsible for analyzing financial data and making recommendations to investors. They must know how to interpret financial statements, build financial models, and value companies. A course in NLP text generation can help you build the skills you need to succeed as a Financial Analyst. In particular, this course teaches you how to use a natural language text generator model to create or predict new text. This skill can be useful for a variety of tasks, such as writing financial reports, developing investment strategies, and creating pitch decks.
Product Manager
Product Manager
Product Managers are responsible for developing and managing products. They must know how to understand customer needs, develop product specifications, and manage product development teams. A course in NLP text generation can help you build the skills you need to succeed as a Product Manager. In particular, this course teaches you how to use a natural language text generator model to create or predict new text. This skill can be useful for a variety of tasks, such as writing product descriptions, developing marketing materials, and creating user documentation.
Operations Manager
Operations Manager
Operations Managers are responsible for planning, organizing, and directing the operations of an organization. They must know how to develop operational plans, manage budgets, and improve efficiency. A course in NLP text generation can help you build the skills you need to succeed as an Operations Manager. In particular, this course teaches you how to use a natural language text generator model to create or predict new text. This skill can be useful for a variety of tasks, such as writing operations manuals, developing process maps, and creating training materials.
Consultant
Consultant
Consultants are responsible for providing advice and guidance to businesses. They must know how to analyze business problems, develop solutions, and communicate their findings. A course in NLP text generation can help you build the skills you need to succeed as a Consultant. In particular, this course teaches you how to use a natural language text generator model to create or predict new text. This skill can be useful for a variety of tasks, such as writing consulting reports, developing presentations, and creating marketing materials.
Technical Writer
Technical Writer
Technical Writers are responsible for writing documentation for technical products. They must know how to write clearly and concisely, and organize information effectively. A course in NLP text generation can help you build the skills you need to succeed as a Technical Writer. In particular, this course teaches you how to use a natural language text generator model to create or predict new text. This skill can be useful for a variety of tasks, such as writing user manuals, developing training materials, and creating marketing documentation.
Customer Success Manager
Customer Success Manager
Customer Success Managers are responsible for ensuring that customers are satisfied with their products or services. They must know how to build relationships with customers, identify customer needs, and resolve customer issues. A course in NLP text generation can help you build the skills you need to succeed as a Customer Success Manager. In particular, this course teaches you how to use a natural language text generator model to create or predict new text. This skill can be useful for a variety of tasks, such as writing customer support articles, developing onboarding materials, and creating customer surveys.
Sales Manager
Sales Manager
Sales Managers are responsible for leading and managing sales teams. They must know how to develop sales strategies, motivate sales teams, and close deals. A course in NLP text generation can help you build the skills you need to succeed as a Sales Manager. In particular, this course teaches you how to use a natural language text generator model to create or predict new text. This skill can be useful for a variety of tasks, such as developing sales presentations, writing sales proposals, and negotiating contracts.
For more career information including salaries, visit:
OpenCourser.com/course/zm5wbb/deploy
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
Deploy an NLP Text Generator: Bart Simpson Chalkboard Gag.
Provides a comprehensive overview of natural language processing, covering topics such as text classification, text clustering, and text generation. It valuable resource for anyone interested in learning more about NLP and its applications.
Save
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 deep learning and its applications.
Provides a practical introduction to text analytics with Python, covering topics such as text preprocessing, text classification, and text clustering. It valuable resource for anyone interested in learning more about text analytics and its applications.
Provides a practical introduction to natural language processing in Python, covering topics such as text preprocessing, text classification, and text generation. It valuable resource for anyone interested in learning more about NLP and its applications.
Provides a comprehensive overview of speech and language processing, covering topics such as speech recognition, natural language understanding, and speech synthesis. It valuable resource for anyone interested in learning more about speech and language processing and its applications.
Provides a comprehensive overview of statistical learning, covering topics such as supervised learning, unsupervised learning, and ensemble methods. It valuable resource for anyone interested in learning more about statistical learning and its applications.
Provides a comprehensive overview of deep learning for natural language processing, covering topics such as word embeddings, convolutional neural networks, and recurrent neural networks. It valuable resource for anyone interested in learning more about deep learning for NLP and its applications.
Save
Provides a comprehensive overview of causal inference, covering topics such as causal diagrams, counterfactuals, and structural equation models. It valuable resource for anyone interested in learning more about causal inference and its applications.
Provides a practical introduction to Bayesian statistics, covering topics such as Bayesian inference, model checking, and hypothesis testing. It valuable resource for anyone interested in learning more about Bayesian statistics and its applications.
Provides a practical introduction to machine learning, covering topics such as supervised learning, unsupervised learning, and deep learning. It valuable resource for anyone interested in learning more about machine learning and its applications.
Provides a practical introduction to data science, covering topics such as data collection, data cleaning, and data analysis. It valuable resource for anyone interested in learning more about data science and its applications.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/zm5wbb/deploy
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Effort
1.5 hours
Level
Intermediate
Via
Coursera
Institution
Coursera Project Network
Instructor
Emmanuel Acheampong
Language
English
Good to know
Fits audience with background in natural language processing
Introduces techniques in natural language processing
Practical application of text generation with Python
Requires familiarity with Git
Requires a Heroku account
Assumes knowledge of Python Streamlit module
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