Course Summary
Learn how to build browser-based models using TensorFlow, a powerful machine learning framework. This course covers the fundamentals of TensorFlow and how to use it to build machine learning models that can run in a web browser.Key Learning Points
- Build and train machine learning models using TensorFlow
- Deploy models to run in a web browser
- Learn how to use TensorFlow.js to build interactive web applications
Related Topics for further study
Learning Outcomes
- Ability to build and train machine learning models using TensorFlow
- Knowledge of how to deploy models to run in a web browser
- Understanding of how to use TensorFlow.js to build interactive web applications
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of machine learning concepts
- Familiarity with JavaScript
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
- Video lectures
- Hands-on exercises
Similar Courses
- Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
- Applied Data Science with Python
Related Education Paths
Notable People in This Field
- Andrew Ng
- François Chollet
Related Books
Description
Bringing a machine learning model into the real world involves a lot more than just modeling. This Specialization will teach you how to navigate various deployment scenarios and use data more effectively to train your model.
Knowledge
- Train and run inference in a browser
- Handle data in a browser
- Build an object classification and recognition model using a webcam
Outline
- Introduction to TensorFlow.js
- Specialization Introduction, A Conversation with Andrew Ng
- Course Introduction, A Conversation with Andrew Ng
- A Few Words From Laurence
- Building the Model
- Training the Model
- First Example In Code
- The Iris Dataset
- Reading the Data
- One-hot Encoding
- Designing the NN
- Iris Classifier In Code
- Getting Your System Ready
- Downloading the Ungraded Labs and Programming Assignments
- Your First Model
- Iris Dataset Documentation
- Using the Web Server
- Iris Classifier
- Week 1 Wrap up
- Image Classification In the Browser
- Introduction, A Conversation with Andrew Ng
- Creating a Convolutional Net with JavaScript
- Visualizing the Training Process
- What Is a Sprite Sheet?
- Using the Sprite Sheet
- Using tf.tidy() to Save Memory
- A Few Words From Laurence
- MNIST Classifier In Code
- tfjs-vis Documentation
- MNIST Sprite Sheet
- MNIST Classifier
- Week 2 Wrap up
- Exercise Description
- Converting Models to JSON Format
- Introduction, A Conversation with Andrew Ng
- A Few Words From Laurence
- Pre-trained TensorFlow.js Models
- Toxicity Classifier
- Toxicity Classifier In Code
- MobileNet
- Using MobileNet
- Training Results
- MobileNet Example In Code
- Converting Models to JavaScript
- Converting Models to JavaScript In Code
- Linear Example In Code
- Important Links
- Toxicity Classifier
- Classes Supported by MobileNet
- Image Classification Using MobileNet
- Linear Model
- Week 3 Wrap up
- Transfer Learning with Pre-Trained Models
- Introduction, A Conversation with Andrew Ng
- A Few Words From Laurence
- Building a Simple Web Page
- Retraining the MobileNet Model
- The Training Function
- Capturing the Data
- The Dataset Class
- Training the Network with the Captured Data
- Performing Inference
- Rock Paper Scissors In Code
- A Conversation with Andrew Ng
- Rock Paper Scissors
- Exercise Description
- Wrap up
Summary of User Reviews
The Browser-based Models with TensorFlow course from Coursera has received positive reviews from students. They have praised the course for its comprehensive and easy-to-follow lessons, as well as its practical approach to learning machine learning. Overall, the course has been highly recommended by many of its users.Key Aspect Users Liked About This Course
The course's practical approach to learning machine learning.Pros from User Reviews
- Comprehensive and easy-to-follow lessons
- Practical approach to learning machine learning
- Great for beginners and those with some experience
- Interactive and engaging content
- Instructors are knowledgeable and helpful
Cons from User Reviews
- Some students found the course to be too basic
- Limited focus on advanced topics
- No opportunity for hands-on experience with TensorFlow
- Course materials could be more organized
- Some technical issues with the platform
Laurence Moroney
4.7 Raiting
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