Create a Superhero Name Generator with TensorFlow from Coursera

Text generation is a common natural language processing task. We will create a character level language model that will predict the next character for a given input sequence. In order to get a new predicted superhero name, we will need to give our model a seed input - this can be a single character or a sequence of characters, and the model will then generate the next character that it predicts should after the input sequence. This character is then added to the seed input to create a new input, which is then used again to generate the next character, and so on.

You will need prior programming experience in Python. Some experience with TensorFlow is recommended. This is a practical, hands on guided project for learners who already have theoretical understanding of Neural Networks, Recurrent Neural Networks, and optimization algorithms like gradient descent but want to understand how to use the TensorFlow to start performing natural language processing tasks like text classification or text generation.

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.

What's inside

Syllabus

Create a Superhero Name Generator with TensorFlow

In this guided project, we are going to create a neural network and train it on a small dataset of superhero names to learn to generate similar names. The dataset has over 9000 names of superheroes, supervillains and other fictional characters from a number of different comic books, TV shows and movies.Text generation is a common natural language processing task. We will create a character level language model that will predict the next character for a given input sequence. In order to get a new predicted superhero name, we will need to give our model a seed input - this can be a single character or a sequence of characters, and the model will then generate the next character that it predicts should after the input sequence. This character is then added to the seed input to create a new input, which is then used again to generate the next character, and so on.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Helps learners develop core skills for deep learning like neural networks, RNN, and optimization algorithms like gradient descent

Provides a practical, hands-on learning experience for learners to create a superhero name generator using TensorFlow

Assumes learners have prior programming experience in Python

Requires some experience with TensorFlow (This is not suitable for learners who are completely new to TensorFlow)

May not be suitable for learners who are not based in the North America region due to potential issues with accessibility

Reviews summary

Tensorflow superhero name generator

Learners say this course provides a guided project on text generation using TensorFlow. Students report that the instructor's explanations are clear and each step of the project is well explained. Prior knowledge of TensorFlow is recommended but not required for this course. Overall, learners report this course is good and that they gained knowledge.

Instructor has clear explanations

"Instructor has a very clear and smooth flow of teaching."

"The way of explaination by lecturers is excellent."

Learners gained knowledge

"I gained more knowledge about machine learning from this project."

"It is Amazing and the way instructor explained the topics is very good and i recommend this course e to solve real problems and to acquire good understanding on machine learning"

Guided project on text generation

"Very educative guided project on text generation."

"Course doen't generate tangible outcome. It leaves you at a hangover. Otherwise this course is good."

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 Create a Superhero Name Generator with TensorFlow with these activities:

Review Python programming fundamentals

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Ensures students have a strong foundation in Python, which is essential for understanding the course material.

Browse courses on Python

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Review Python syntax, data structures, and algorithms.
Complete coding exercises to practice Python programming.

Read 'TensorFlow for Deep Learning' by Bharath Ramsundar

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Provides a thorough grounding in TensorFlow, the open-source machine learning library used in this course.

View Deep Learning for the Life Sciences on Amazon

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Read Chapters 1-3 to gain an overview of TensorFlow and its core concepts.
Work through the tutorials in Chapter 4 to practice building and training neural networks.

Participate in a study group to discuss course concepts and work on assignments

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Provides opportunities for collaboration, peer learning, and reinforcement of course material.

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Find or form a study group with other course participants.
Meet regularly to discuss course material, work on assignments, and quiz each other.

Five other activities

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Complete the TensorFlow “Neural Machine Translation with Attention” tutorial

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Provides hands-on experience with a real-world NLP application, providing context for the course material.

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Follow the steps in the tutorial to build a neural machine translation model.
Experiment with different hyperparameters to optimize model performance.

Solve coding challenges on LeetCode related to natural language processing

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Provides targeted practice in applying NLP techniques to solve real-world problems.

Browse courses on Natural Language Processing

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Identify LeetCode problems tagged with 'NLP' or 'Natural Language Processing'.
Solve the problems using techniques covered in the course.

Create a blog post explaining the concept of recurrent neural networks

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Encourages deep understanding of RNNs by requiring students to explain them in their own words.

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Research recurrent neural networks and identify key concepts.
Write a blog post that clearly explains these concepts and provides examples.

Develop a simple Python script to generate superhero names using the techniques learned in the course

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Provides practical application of course material and allows students to demonstrate their understanding.

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Implement a character-level language model using TensorFlow.
Train the model on the superhero name dataset.
Create a function to generate new superhero names.

Contribute to an open-source NLP project on GitHub

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Provides exposure to real-world NLP projects and encourages collaboration within the NLP community.

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Identify an open-source NLP project on GitHub that aligns with your interests.
Read the project documentation and identify areas where you can contribute.
Submit a pull request with your contributions.

Career center

Learners who complete Create a Superhero Name Generator with TensorFlow will develop knowledge and skills that may be useful to these careers:

Natural Language Processing Engineer

Natural Language Processing Engineers develop and maintain natural language processing models that can be used to understand and generate text. This course can help build a foundation in natural language processing, which is a key skill for Natural Language Processing Engineers. The course also covers how to use TensorFlow, which is a popular framework for building and training deep learning models. This knowledge can be helpful for Natural Language Processing Engineers who want to develop new and innovative natural language processing models.

See salaries and explore the career path for Natural Language Processing Engineer

Machine Learning Engineer

Machine Learning Engineers build and maintain machine learning models that can be used to automate tasks and improve decision-making. This course can help build a foundation in natural language processing, which is a key skill for developing machine learning models that can understand and generate text. The course also covers how to use TensorFlow, which is a popular framework for building and training deep learning models. This knowledge can be helpful for Machine Learning Engineers who want to develop new and innovative machine learning models that use natural language processing.

See salaries and explore the career path for Machine Learning Engineer

Data Scientist

Data Scientists use their knowledge of data analysis, machine learning and statistics to extract insights from data that can be used to solve business problems. This course can help build a foundation in natural language processing, which is a key skill for extracting insights from text data. The course also covers how to use TensorFlow, which is a popular framework for building and training deep learning models. This knowledge can be helpful for Data Scientists who want to develop new and innovative ways to solve business problems using natural language processing.

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Data Analyst

Data Analysts use their knowledge of data analysis, statistics, and machine learning to extract insights from data. This course can help build a foundation in natural language processing, which is a key skill for extracting insights from text data. The course also covers how to use TensorFlow, which is a popular framework for building and training deep learning models. This knowledge can be helpful for Data Analysts who want to develop new and innovative ways to extract insights from text data.

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Product Manager

Product Managers are responsible for managing the development and launch of new products. This course can help build a foundation in natural language processing, which is a key skill for understanding and analyzing customer feedback. The course also covers how to use TensorFlow, which is a popular framework for building and training deep learning models. This knowledge can be helpful for Product Managers who want to develop new and innovative products that meet the needs of customers.

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Instructional Designer

Instructional Designers create and maintain instructional materials, such as online courses, training manuals, and workshops. This course can help build a foundation in natural language processing, which is a key skill for writing clear and concise instructional materials. The course also covers how to use TensorFlow, which is a popular framework for building and training deep learning models. This knowledge can be helpful for Instructional Designers who want to develop new and innovative ways to create and maintain instructional materials.

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Technical Writer

Technical Writers create and maintain technical documentation, such as user manuals, white papers, and training materials. This course can help build a foundation in natural language processing, which is a key skill for writing clear and concise technical documentation. The course also covers how to use TensorFlow, which is a popular framework for building and training deep learning models. This knowledge can be helpful for Technical Writers who want to develop new and innovative ways to create and maintain technical documentation.

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Customer Success Manager

Customer Success Managers are responsible for ensuring that customers are successful with a company's products or services. This course can help build a foundation in natural language processing, which is a key skill for understanding and analyzing customer feedback. The course also covers how to use TensorFlow, which is a popular framework for building and training deep learning models. This knowledge can be helpful for Customer Success Managers who want to develop new and innovative ways to improve customer satisfaction and retention.

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UX Writer

UX Writers create and maintain user experience (UX) content, such as website navigation, error messages, and tooltips. This course can help build a foundation in natural language processing, which is a key skill for writing clear and concise UX content. The course also covers how to use TensorFlow, which is a popular framework for building and training deep learning models. This knowledge can be helpful for UX Writers who want to develop new and innovative ways to create and maintain UX content.

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Copywriter

Copywriters create and maintain marketing and advertising copy. This course can help build a foundation in natural language processing, which is a key skill for writing clear and concise copy. The course also covers how to use TensorFlow, which is a popular framework for building and training deep learning models. This knowledge can be helpful for Copywriters who want to develop new and innovative ways to create and maintain marketing and advertising copy.

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Marketing Manager

Marketing Managers are responsible for developing and executing marketing campaigns. This course can help build a foundation in natural language processing, which is a key skill for understanding and analyzing customer behavior. The course also covers how to use TensorFlow, which is a popular framework for building and training deep learning models. This knowledge can be helpful for Marketing Managers who want to develop new and innovative marketing campaigns that reach and engage customers.

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Content Writer

Content Writers create and maintain content for websites, blogs, and other online platforms. This course can help build a foundation in natural language processing, which is a key skill for writing clear and concise content. The course also covers how to use TensorFlow, which is a popular framework for building and training deep learning models. This knowledge can be helpful for Content Writers who want to develop new and innovative ways to create and maintain content.

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Sales Manager

Sales Managers are responsible for managing sales teams and developing sales strategies. This course can help build a foundation in natural language processing, which is a key skill for understanding and analyzing customer needs. The course also covers how to use TensorFlow, which is a popular framework for building and training deep learning models. This knowledge can be helpful for Sales Managers who want to develop new and innovative sales strategies that close deals and grow revenue.

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Business Analyst

Business Analysts use their knowledge of business processes and data analysis to help organizations improve their performance. This course can help build a foundation in natural language processing, which is a key skill for understanding and analyzing business text data. The course also covers how to use TensorFlow, which is a popular framework for building and training deep learning models. This knowledge can be helpful for Business Analysts who want to develop new and innovative ways to improve organizational performance using natural language processing.

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Software Engineer

Software Engineers design, develop, and maintain software systems. This course can help build a foundation in natural language processing, which is a key skill for developing software systems that can understand and generate text. The course also covers how to use TensorFlow, which is a popular framework for building and training deep learning models. This knowledge can be helpful for Software Engineers who want to develop new and innovative software systems that use natural language processing.

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