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Vinita Silaparasetty
Note: The rhyme platform currently does not support webcams, so this is not a live project.
This guided project is about human activity recognition using Python,TensorFlow2 and Keras. Human activity recognition comes under the computer vision domain. In...
Read more
Note: The rhyme platform currently does not support webcams, so this is not a live project.
This guided project is about human activity recognition using Python,TensorFlow2 and Keras. Human activity recognition comes under the computer vision domain. In...
Read more
Note: The rhyme platform currently does not support webcams, so this is not a live project.
This guided project is about human activity recognition using Python,TensorFlow2 and Keras. Human activity recognition comes under the computer vision domain. In this project you will learn how to customize the InceptionNet model using Tensorflow2 and Keras.
While you are watching me code, you will get a cloud desktop with all the required software pre-installed. This will allow you to code along with me. After all, we learn best with active, hands-on learning.
Special Feature:
1.Manually label images.
2. Learn how to use data augmentation normalization.
3. Learn about transfer learning using training the pre-trained model InceptionNet V3 on the data.
Note: This project 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/5rotmk/activity
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Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Teaches techniques that are standard in computer vision
Shows how to apply InceptionNet, a pre-trained model
Excellent for learners based in North America
Provides a hands-on learning experience with a cloud desktop
Save this course
Save Activity Recognition using Python, Tensorflow and Keras to your list so you can find it easily later:
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Reviews summary
Inception activity recognition
This course uses the Inception model for deep learning and TensorFlow. It covers data augmentation and normalization and manually labeling images. However, it lacks support for webcams and the videos may need improvement. Some of the code written is not at a high level of competence.
Uses the Inception model for recognition
"...learn how to customize the InceptionNet model using Tensorflow2 and Keras."
Low level of code competence
"I've not seen code written so incompetently."
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 Activity Recognition using Python, Tensorflow and Keras with these
activities:
Study Group for the Course
Show steps
Join or create a study group with other students in the course to discuss the material and help each other learn.
Show steps
-
Find or create a study group
-
Meet regularly to discuss the course material
Tensorflow2 Tutorials
Show steps
This tutorial will help you familiarize with Tensorflow2 and the InceptionNet model used in the course.
Browse courses on
Transfer Learning
Show steps
-
Follow along with the video tutorial on setting up Tensorflow2
-
Follow along with the video tutorial on using the InceptionNet model
InceptionNet Practice
Show steps
Practice customizing the InceptionNet model on your own dataset.
Show steps
-
Find and download a dataset
-
Pre-process the data
-
Customize the InceptionNet model
-
Train and evaluate the model
One other activity
Expand to see all activities and additional details
Show all four activities
Blog Post on Human Activity Recognition
Show steps
Share your learning and insights about human activity recognition by writing a blog post.
Show steps
-
Choose a topic
-
Write an outline
-
Write the blog post
Study Group for the Course
Show steps
Join or create a study group with other students in the course to discuss the material and help each other learn.
Show steps
Show steps
Show steps
- Find or create a study group
- Meet regularly to discuss the course material
Tensorflow2 Tutorials
Show steps
This tutorial will help you familiarize with Tensorflow2 and the InceptionNet model used in the course.
Browse courses on
Transfer Learning
Show steps
Show steps
Show steps
- Follow along with the video tutorial on setting up Tensorflow2
- Follow along with the video tutorial on using the InceptionNet model
InceptionNet Practice
Show steps
Practice customizing the InceptionNet model on your own dataset.
Show steps
Show steps
Show steps
- Find and download a dataset
- Pre-process the data
- Customize the InceptionNet model
- Train and evaluate the model
One other activity
Expand to see all activities and additional details
Show all four activities
Blog Post on Human Activity Recognition
Show steps
Share your learning and insights about human activity recognition by writing a blog post.
Show steps
Show steps
Show steps
- Choose a topic
- Write an outline
- Write the blog post
Career center
Learners who complete Activity Recognition using Python, Tensorflow and Keras will develop knowledge and skills
that may be useful to these careers:
Computer Vision Engineer
Computer Vision Engineer
A Computer Vision Engineer is responsible for developing and implementing computer vision systems. This course may be useful in role because it provides hands-on experience with data augmentation, normalization, and transfer learning, all of which are essential techniques in computer vision.
Machine Learning Engineer
Machine Learning Engineer
A Machine Learning Engineer is responsible for designing, building, and deploying machine learning models. This course may be useful in role because it teaches you how to customize the InceptionNet model using TensorFlow2 and Keras. This can be useful in creating powerful models for machine learning.
Software Engineer
Software Engineer
A Software Engineer is responsible for designing, developing, and maintaining software systems. This course may be useful in role because it provides hands-on experience with Python, TensorFlow2, and Keras, all of which are popular tools for software development.
Data Analyst
Data Analyst
A Data Analyst is responsible for collecting, cleaning, and analyzing data to find insights and trends. This course may be useful in role because it provides hands-on experience with data augmentation, normalization, and transfer learning, all of which are essential techniques in data analysis.
Network Administrator
Network Administrator
A Network Administrator is responsible for planning, implementing, and maintaining an organization's computer networks. This course may be useful in role because it provides hands-on experience with data augmentation, normalization, and transfer learning, all of which are essential techniques in network administration.
Information Security Analyst
Information Security Analyst
An Information Security Analyst is responsible for protecting an organization's information systems from unauthorized access, use, disclosure, disruption, modification, or destruction. This course may be useful in role because it provides hands-on experience with data augmentation, normalization, and transfer learning, all of which are essential techniques in information security.
Product Manager
Product Manager
A Product Manager is responsible for planning, developing, and launching new products. This course may be useful in role because it provides hands-on experience with data augmentation, normalization, and transfer learning, all of which are essential techniques in product management.
IT Manager
IT Manager
An IT Manager is responsible for planning, implementing, and managing an organization's information technology (IT) systems. This course may be useful in role because it provides hands-on experience with data augmentation, normalization, and transfer learning, all of which are essential techniques in IT management.
Systems Administrator
Systems Administrator
A Systems Administrator is responsible for planning, implementing, and maintaining an organization's computer systems. This course may be useful in role because it provides hands-on experience with data augmentation, normalization, and transfer learning, all of which are essential techniques in systems administration.
User Experience Designer
User Experience Designer
A User Experience Designer is responsible for designing and evaluating user interfaces. This course may be useful in role because it provides hands-on experience with data augmentation, normalization, and transfer learning, all of which are essential techniques in user experience design.
Project Manager
Project Manager
A Project Manager is responsible for planning, executing, and closing projects. This course may be useful in role because it provides hands-on experience with data augmentation, normalization, and transfer learning, all of which are essential techniques in project management.
Quality Assurance Analyst
Quality Assurance Analyst
A Quality Assurance Analyst is responsible for testing and validating software systems. This course may be useful in role because it provides hands-on experience with data augmentation, normalization, and transfer learning, all of which are essential techniques in quality assurance.
Data Scientist
Data Scientist
A Data Scientist is responsible for collecting and analyzing data to find insights and trends. Often times this data is presented by visualization to illustrate the meaning and to find patterns. This course may be useful in role because it teaches data augmentation, which is a method of preparing data to be trained on by machines. Being able to put machine learning models into practice is a valuable skill in data science.
Business Analyst
Business Analyst
A Business Analyst is responsible for analyzing business processes and identifying opportunities for improvement. This course may be useful in role because it provides hands-on experience with data augmentation, normalization, and transfer learning, all of which are essential techniques in business analysis.
Database Administrator
Database Administrator
A Database Administrator is responsible for planning, implementing, and maintaining an organization's database systems. This course may be useful in role because it provides hands-on experience with data augmentation, normalization, and transfer learning, all of which are essential techniques in database administration.
For more career information including salaries, visit:
OpenCourser.com/course/5rotmk/activity
Reading list
We've selected six 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
Activity Recognition using Python, Tensorflow and Keras .
Provides a comprehensive overview of deep learning, from the basics to advanced techniques. It is written in a clear and concise style, and it is packed with practical examples and exercises.
Provides a practical guide to machine learning using Python. It covers a wide range of topics, from data preprocessing to model evaluation. It valuable resource for anyone who wants to learn more about machine learning.
Provides a collection of recipes for common TensorFlow 2.0 tasks. It covers a wide range of topics, from data loading to model training. It valuable resource for anyone who wants to learn more about TensorFlow 2.0.
Provides a comprehensive overview of computer vision. It covers a wide range of topics, from image processing to object detection. It valuable resource for anyone who wants to learn more about computer vision.
Provides a practical guide to deep learning for computer vision. It covers a wide range of topics, from image processing to object detection. It valuable resource for anyone who wants to learn more about deep learning for computer vision.
Save
Provides a comprehensive overview of human motion tracking and analysis. It covers a wide range of topics, from motion capture to data analysis. It valuable resource for anyone who wants to learn more about human motion tracking and analysis.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/5rotmk/activity
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Time
1 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Vinita Silaparasetty
Good to know
Teaches techniques that are standard in computer vision
Shows how to apply InceptionNet, a pre-trained model
Excellent for learners based in North America
Provides a hands-on learning experience with a cloud desktop
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