Course Summary
This course teaches Natural Language Processing using TensorFlow. You will learn how to build and train models for common NLP tasks such as sentiment analysis and language generation.Key Learning Points
- Build and train models for common NLP tasks using TensorFlow
- Understand the concepts behind Natural Language Processing
- Apply NLP techniques to real-world problems
Job Positions & Salaries of people who have taken this course might have
- USA: $107,000
- India: ₹1,200,000
- Spain: €45,000
- USA: $107,000
- India: ₹1,200,000
- Spain: €45,000
- USA: $117,000
- India: ₹1,500,000
- Spain: €50,000
- USA: $107,000
- India: ₹1,200,000
- Spain: €45,000
- USA: $117,000
- India: ₹1,500,000
- Spain: €50,000
- USA: $143,000
- India: ₹2,000,000
- Spain: €70,000
Related Topics for further study
Learning Outcomes
- Build and train NLP models using TensorFlow
- Apply NLP techniques to real-world problems
- Understand the fundamentals of NLP
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of Python
- Familiarity with machine learning concepts
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
- Video lectures
- Hands-on exercises
Similar Courses
- Applied Data Science with Python
- Machine Learning
Related Education Paths
Notable People in This Field
- AI researcher, Google
- Founder, deeplearning.ai
Related Books
Description
If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.
Knowledge
- Build natural language processing systems using TensorFlow
- Process text, including tokenization and representing sentences as vectors
- Apply RNNs, GRUs, and LSTMs in TensorFlow
- Train LSTMs on existing text to create original poetry and more
Outline
- Sentiment in text
- Introduction, A conversation with Andrew Ng
- Introduction
- Word based encodings
- Using APIs
- Notebook for lesson 1
- Text to sequence
- Looking more at the Tokenizer
- Padding
- Notebook for lesson 2
- Sarcasm, really?
- Working with the Tokenizer
- Notebook for lesson 3
- Week 1 Wrap up
- Check out the code!
- Check out the code!
- News headlines dataset for sarcasm detection
- Check out the code!
- Word Embeddings
- A conversation with Andrew Ng
- Introduction
- The IMBD dataset
- Looking into the details
- How can we use vectors?
- More into the details
- Notebook for lesson 1
- Remember the sarcasm dataset?
- Building a classifier for the sarcasm dataset
- Let’s talk about the loss function
- Pre-tokenized datasets
- Diving into the code (part 1)
- Diving into the code (part 2)
- Notebook for lesson 3
- IMDB reviews dataset
- Check out the code!
- Check out the code!
- TensorFlow datasets
- Subwords text encoder
- Check out the code!
- Week 2 Wrap up
- Sequence models
- A conversation with Andrew Ng
- Introduction
- LSTMs
- Implementing LSTMs in code
- Accuracy and loss
- A word from Laurence
- Looking into the code
- Using a convolutional network
- Going back to the IMDB dataset
- Tips from Laurence
- Link to Andrew's sequence modeling course
- More info on LSTMs
- Check out the code!
- Check out the code!
- Check out the code!
- Exploring different sequence models
- Week 3 Wrap up
- Sequence models and literature
- A conversation with Andrew Ng
- Introduction
- Looking into the code
- Training the data
- More on training the data
- Notebook for lesson 1
- Finding what the next word should be
- Example
- Predicting a word
- Poetry!
- Looking into the code
- Laurence the poet!
- Your next task
- A conversation with Andrew Ng
- Check out the code!
- link to Laurence's poetry
- Check out the code!
- Link to generating text using a character-based RNN
- Wrap up
Summary of User Reviews
Discover the power of Natural Language Processing with TensorFlow in this highly rated course on Coursera. Users rave about the course, praising its hands-on approach and real-world applications.Key Aspect Users Liked About This Course
The hands-on approach and real-world applications of the course are highly praised by many users.Pros from User Reviews
- The course provides a great introduction to Natural Language Processing and TensorFlow.
- The instructors are knowledgeable and engaging.
- The hands-on exercises are challenging but rewarding.
- The course covers a wide range of topics in NLP and TensorFlow.
- The real-world applications of NLP and TensorFlow are emphasized throughout the course.
Cons from User Reviews
- Some users found the pace of the course to be too fast.
- The course requires a basic understanding of Python programming.
- The course may be too technical for some users.
- The course does not cover advanced topics in NLP and TensorFlow.
- The course may not be suitable for users who are looking for a more theoretical approach to NLP.
Laurence Moroney
4.6 Raiting
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