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Vinita Silaparasetty
Note: The rhyme platform currently does not support webcams, so this is not a live hand gesture recognition project.
This guided project is about hand gesture recognition using Python,TensorFlow2 and Keras. Hand gesture recognition comes under the computer...
Read more
Note: The rhyme platform currently does not support webcams, so this is not a live hand gesture recognition project.
This guided project is about hand gesture recognition using Python,TensorFlow2 and Keras. Hand gesture recognition comes under the computer...
Read more
Note: The rhyme platform currently does not support webcams, so this is not a live hand gesture recognition project.
This guided project is about hand gesture recognition using Python,TensorFlow2 and Keras. Hand gesture recognition comes under the computer vision domain. In this project you will learn how to build a convolutional neural network(CNN) 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) Learn about data augmentation.
2) How to reshape data to fit a CNN.
3) Explanation of each layer in a CNN.
4) Create a Streamlit app to allow users to select a hand gesture and obtain the alphabet it represents using the model you trained.
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/fe3hqg/hand
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Helps learners implement hand gesture recognition using Python, TensorFlow 2, and Keras, which are in-demand skills for computer vision
Develops skills in data augmentation, reshaping data for CNNs, and understanding CNN layers, which are core skills for computer vision
Includes a hands-on project that allows learners to create a Streamlit app for hand gesture recognition, providing practical experience
Teaches state-of-the-art techniques in computer vision, making it relevant for learners aiming to keep up with the industry
Taught by Vinita Silaparasetty, an experienced instructor in computer vision and data science
Suitable for learners based in the North America region only, which may be a limitation for learners in other regions
Save this course
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Reviews summary
Tensorflow hand gesture recognition
The one reviewed Tensorflow and Keras course is well received. It has earned five stars from two reviews and four from one review. Students who took this project-based course recommend it as a starting point for intermediate learners of deep learning. One review suggests that the course content may be better ordered.
Deep learning project for intermediates
"This is an amazing project, every deep learning intermediate may start with this."
Course flow could be improved
"The course is not ordered well. Data Processing should come second."
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 Hand Gesture Recognition using Tensorflow and Keras with these
activities:
Review Python programming fundamentals
Show steps
Strengthen your foundation in Python programming by reviewing key concepts and practicing basic coding tasks.
Browse courses on
Python Programming
Show steps
-
Revisit the basics of Python syntax, data types, and variables.
-
Solve simple Python coding problems to reinforce your understanding.
Brush up on linear algebra and calculus
Show steps
Ensure a solid foundation in linear algebra and calculus by reviewing key concepts and practicing problem-solving.
Browse courses on
Linear Algebra
Show steps
-
Review basic linear algebra concepts like vectors, matrices, and matrix operations.
-
Revisit fundamental calculus concepts such as derivatives and integrals.
Read 'Computer Vision: Algorithms and Applications'
Show steps
Expand your knowledge of computer vision and image processing by reading a comprehensive book that covers algorithms and applications relevant to hand gesture recognition.
View
Computer Vision
on Amazon
Show steps
-
Read selected chapters from the book that focus on gesture recognition.
-
Summarize key concepts and techniques discussed in the book.
Three other activities
Expand to see all activities and additional details
Show all six activities
Practice gesture recognition tasks
Show steps
Reinforce your understanding of hand gesture recognition techniques by practicing different tasks related to this concept.
Browse courses on
Gesture Recognition
Show steps
-
Identify and label different hand gestures using a provided dataset.
-
Develop a simple CNN model to classify hand gestures.
Explore advanced gesture recognition techniques
Show steps
Enhance your knowledge of gesture recognition by exploring cutting-edge techniques and expanding your understanding of the field.
Browse courses on
Convolutional Neural Networks
Show steps
-
Research state-of-the-art gesture recognition algorithms.
-
Implement a more sophisticated CNN model for hand gesture classification.
Collaborate on a gesture recognition project
Show steps
Deepen your understanding of gesture recognition by working with peers on a collaborative project that involves implementing and evaluating a hand gesture recognition system.
Browse courses on
Teamwork
Show steps
-
Form a team with other students and define the project scope.
-
Design and implement a CNN model for the project.
-
Evaluate the performance of the model and explore ways to improve it.
Review Python programming fundamentals
Show steps
Strengthen your foundation in Python programming by reviewing key concepts and practicing basic coding tasks.
Browse courses on
Python Programming
Show steps
Show steps
Show steps
- Revisit the basics of Python syntax, data types, and variables.
- Solve simple Python coding problems to reinforce your understanding.
Brush up on linear algebra and calculus
Show steps
Ensure a solid foundation in linear algebra and calculus by reviewing key concepts and practicing problem-solving.
Browse courses on
Linear Algebra
Show steps
Show steps
Show steps
- Review basic linear algebra concepts like vectors, matrices, and matrix operations.
- Revisit fundamental calculus concepts such as derivatives and integrals.
Read 'Computer Vision: Algorithms and Applications'
Show steps
Expand your knowledge of computer vision and image processing by reading a comprehensive book that covers algorithms and applications relevant to hand gesture recognition.
View
Computer Vision
on Amazon
Show steps
Show steps
Show steps
- Read selected chapters from the book that focus on gesture recognition.
- Summarize key concepts and techniques discussed in the book.
Three other activities
Expand to see all activities and additional details
Show all six activities
Practice gesture recognition tasks
Show steps
Reinforce your understanding of hand gesture recognition techniques by practicing different tasks related to this concept.
Browse courses on
Gesture Recognition
Show steps
Show steps
Show steps
- Identify and label different hand gestures using a provided dataset.
- Develop a simple CNN model to classify hand gestures.
Explore advanced gesture recognition techniques
Show steps
Enhance your knowledge of gesture recognition by exploring cutting-edge techniques and expanding your understanding of the field.
Browse courses on
Convolutional Neural Networks
Show steps
Show steps
Show steps
- Research state-of-the-art gesture recognition algorithms.
- Implement a more sophisticated CNN model for hand gesture classification.
Collaborate on a gesture recognition project
Show steps
Deepen your understanding of gesture recognition by working with peers on a collaborative project that involves implementing and evaluating a hand gesture recognition system.
Browse courses on
Teamwork
Show steps
Show steps
Show steps
- Form a team with other students and define the project scope.
- Design and implement a CNN model for the project.
- Evaluate the performance of the model and explore ways to improve it.
Career center
Learners who complete Hand Gesture Recognition using Tensorflow and Keras will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data scientists build models that are used to make decisions in a wide range of industries. They use mathematical and statistical techniques to analyze data, which allows them to identify trends and patterns that can be used to make better decisions. Those with a background in the Python programming language will have a strong advantage in this field. Additionally, a course like this one on TensorFlow and Keras can help data scientists build deep learning models which employ CNNs.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers develop and improve systems that can interpret and understand images and videos. They use machine learning algorithms to train computers to recognize objects, faces, and other features in images. This course on Hand Gesture Recognition using TensorFlow and Keras can help build an excellent foundation for this career path. It provides hands-on experience in building a CNN-based model for hand gesture recognition using TensorFlow and Keras.
Research Scientist
Research Scientist
Research Scientists conduct research in a wide range of fields, including computer science, biology, and physics. They use their expertise in machine learning and other disciplines to develop new technologies and solve complex problems. This course can be an important stepping stone for those wishing to pursue this career. It provides a grounding in the fundamentals of machine learning and computer vision, which are essential skills for Research Scientists.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They use their programming skills to create software that meets the needs of users. A grounding in machine learning can provide an advantage in this field. This course on TensorFlow and Keras can also help Software Engineers develop deep learning models that can be incorporated into their software applications.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design and develop machine learning models. They use their expertise in machine learning algorithms to create models that can learn from data and make predictions. A course on Hand Gesture Recognition using TensorFlow and Keras can provide a valuable background for those wishing to enter this field. The course covers the fundamentals of machine learning and deep learning and provides hands-on experience in developing and deploying machine learning models.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to help businesses make better decisions. They use their statistical and programming skills to identify trends and patterns in data. This course on TensorFlow and Keras can provide a strong foundation for those wishing to enter this field. It provides hands-on experience in building a deep learning model for hand gesture recognition, which can be applied to a wide range of data analysis tasks.
Business Analyst
Business Analyst
Business Analysts help businesses understand their data and make better decisions. They use their analytical skills to identify problems and opportunities, and they develop recommendations to improve business performance. A course on TensorFlow and Keras can provide a strong foundation for those wishing to enter this field. It provides hands-on experience in building a deep learning model for hand gesture recognition, which can be applied to a wide range of business analysis tasks.
Product Manager
Product Manager
Product Managers are responsible for the development and management of products. They work with engineers, designers, and marketers to bring products to market. This course on TensorFlow and Keras can provide a valuable background for those wishing to enter this field. It provides hands-on experience in building a deep learning model for hand gesture recognition, which can be applied to a wide range of product development tasks.
Project Manager
Project Manager
Project Managers plan, execute, and close projects. They work with teams of people to achieve project goals. This course on TensorFlow and Keras can provide a valuable skill set for those wishing to enter this field. It provides hands-on experience in building a deep learning model for hand gesture recognition, which can be applied to a wide range of project management tasks.
Consultant
Consultant
Consultants provide advice and guidance to businesses. They use their expertise in a particular field to help businesses solve problems and improve performance. This course on TensorFlow and Keras can provide a valuable background for those wishing to enter this field. It provides hands-on experience in building a deep learning model for hand gesture recognition, which can be applied to a wide range of consulting tasks.
Teacher
Teacher
Teachers help students learn and grow. They develop lesson plans, deliver instruction, and assess student learning. This course on TensorFlow and Keras can provide a valuable background for those wishing to enter this field. It provides hands-on experience in building a deep learning model for hand gesture recognition, which can be applied to a wide range of teaching tasks.
Technical Writer
Technical Writer
Technical Writers create technical documentation, such as user manuals, technical reports, and white papers. They use their writing skills to explain complex technical concepts in a clear and concise way. This course on TensorFlow and Keras can provide a valuable background for those wishing to enter this field. It provides hands-on experience in building a deep learning model for hand gesture recognition, which can be applied to a wide range of technical writing tasks.
UX Designer
UX Designer
UX Designers design the user experience for websites, apps, and other products. They use their knowledge of human behavior and design principles to create products that are easy to use and enjoyable. This course on TensorFlow and Keras can provide a valuable background for those wishing to enter this field. It provides hands-on experience in building a deep learning model for hand gesture recognition, which can be applied to a wide range of UX design tasks.
UI Designer
UI Designer
UI Designers design the user interface for websites, apps, and other products. They use their knowledge of visual design principles to create products that are aesthetically pleasing and easy to use. This course on TensorFlow and Keras can provide a valuable background for those wishing to enter this field. It provides hands-on experience in building a deep learning model for hand gesture recognition, which can be applied to a wide range of UI design tasks.
Front-End Developer
Front-End Developer
Front-End Developers develop the user interface for websites and apps. They use their knowledge of HTML, CSS, and JavaScript to create products that are visually appealing and easy to use. This course on TensorFlow and Keras can provide a valuable background for those wishing to enter this field. It provides hands-on experience in building a deep learning model for hand gesture recognition, which can be applied to a wide range of front-end development tasks.
For more career information including salaries, visit:
OpenCourser.com/course/fe3hqg/hand
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
Hand Gesture Recognition using Tensorflow and Keras.
Save
Practical guide to machine learning using popular Python libraries.
In-depth study of computer vision, covering CNNs, object detection, and segmentation.
Provides a comprehensive overview of computer vision and its applications, including image classification, object detection, and segmentation. It good resource for learners who want to learn how to use Keras to build computer vision models.
Easy-to-follow introduction with code examples.
Comprehensive textbook covering a wide range of computer vision topics.
Provides a practical introduction to machine learning using Scikit-Learn, Keras, and TensorFlow. It good resource for learners who want to learn how to build and train machine learning models.
Provides a comprehensive overview of deep learning for computer vision. It good resource for learners who want to learn how to build and train deep learning models for computer vision tasks.
Provides a comprehensive overview of pattern recognition and machine learning. It good resource for learners who want to gain a deeper understanding of the theory and practice of machine learning.
Provides a probabilistic perspective on machine learning. It good resource for learners who want to gain a deeper understanding of the theory of machine learning.
Provides a gentle introduction to machine learning. It good resource for learners who are new to the field.
Provides a comprehensive overview of Keras. It good resource for learners who want to learn how to use Keras to build and train deep learning models.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/fe3hqg/hand
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Coursera
Institution
Coursera Project Network
Instructor
Vinita Silaparasetty
Good to know
Helps learners implement hand gesture recognition using Python, TensorFlow 2, and Keras, which are in-demand skills for computer vision
Develops skills in data augmentation, reshaping data for CNNs, and understanding CNN layers, which are core skills for computer vision
Includes a hands-on project that allows learners to create a Streamlit app for hand gesture recognition, providing practical experience
Teaches state-of-the-art techniques in computer vision, making it relevant for learners aiming to keep up with the industry
Taught by Vinita Silaparasetty, an experienced instructor in computer vision and data science
Suitable for learners based in the North America region only, which may be a limitation for learners in other regions
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