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Sebastian Thrun,
Cezanne Camacho,
Jay Alammar,
Alexis Cook,
Luis Serrano,
Juan Delgado,
and
Ortal Arel
Take a quick look at a few really cool applications of deep learning and computer vision, such as Neural Style Transfer, that using pre-trained models.
Register for this course and see more details by visiting:
OpenCourser.com/course/ga4eo5/applications
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What's inside
Syllabus
Try out a few really cool applications of computer vision and deep learning, such as style transfer, using pre-trained models that others have generously provided on Github.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Develops deep learning skills through practical projects
Taught by industry leaders in deep learning and computer vision
Highly relevant to current industry practices in deep learning and computer vision
Suitable for students with a strong foundation in deep learning and computer vision
Focuses on pre-trained models, which may limit exploration of custom model building
Save this course
Save Applications of Computer Vision & Deep Learning to your list so you can find it easily later:
Save
Save
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 Applications of Computer Vision & Deep Learning with these
activities:
Connect with Mentors
Show steps
Seek guidance and support from experienced professionals in the field of Neural Style Transfer.
Show steps
-
Identify potential mentors who have expertise in Neural Style Transfer
-
Reach out to them and express your interest in mentorship
-
Regularly connect with your mentors for advice and feedback
Participate in a Study Group
Show steps
Find a peer study group to discuss your understanding of Neural Style Transfer, collaborate on projects, and support each other's learning.
Show steps
-
Find like-minded individuals who are also interested in Neural Style Transfer
-
Schedule regular study sessions
-
Share knowledge, ideas, and resources with each other
Follow a Tutorial on Neural Style Transfer
Show steps
Supplement your theoretical knowledge by following a guided tutorial that provides step-by-step instructions for implementing Neural Style Transfer.
Show steps
-
Locate a comprehensive tutorial that covers the implementation of Neural Style Transfer
-
Follow the instructions in the tutorial carefully
-
Troubleshoot any issues that may arise during the implementation
Five other activities
Expand to see all activities and additional details
Show all eight activities
Attend a Workshop on Neural Style Transfer
Show steps
Advance your skills by attending a workshop dedicated to Neural Style Transfer, led by experts in the field.
Show steps
-
Research and find workshops on Neural Style Transfer
-
Register for a workshop that fits your schedule and interests
-
Attend the workshop and actively participate in discussions and activities
Create a Neural Style Transfer Application
Show steps
Reinforce your understanding of Neural Style Transfer by building a simple application that demonstrates the technique's capabilities.
Browse courses on
Neural Style Transfer
Show steps
-
Set up the necessary environment and libraries for developing the application
-
Gather a dataset of images to be used for style transfer
-
Implement the Neural Style Transfer algorithm
-
Evaluate the performance of your application on the dataset
Contribute to Open-Source Projects
Show steps
Gain practical experience and deepen your understanding by contributing to open-source projects related to Neural Style Transfer.
Show steps
-
Identify open-source projects in the field of Neural Style Transfer
-
Choose a project that aligns with your skills and interests
-
Contribute code, documentation, or other resources to the project
Develop a Neural Style Transfer App
Show steps
Demonstrate your mastery of Neural Style Transfer by creating a fully functional application that incorporates the technique.
Show steps
-
Design the architecture and user interface of your application
-
Integrate the Neural Style Transfer algorithm into your application
-
Implement features for user interaction and image manipulation
-
Test and deploy your application
Participate in a Neural Style Transfer Competition
Show steps
Challenge yourself and test your skills by participating in a competition that focuses on Neural Style Transfer techniques.
Show steps
-
Research and identify competitions that are relevant to Neural Style Transfer
-
Develop an innovative approach to Neural Style Transfer
-
Submit your work to the competition
Connect with Mentors
Show steps
Seek guidance and support from experienced professionals in the field of Neural Style Transfer.
Show steps
Show steps
Show steps
- Identify potential mentors who have expertise in Neural Style Transfer
- Reach out to them and express your interest in mentorship
- Regularly connect with your mentors for advice and feedback
Participate in a Study Group
Show steps
Find a peer study group to discuss your understanding of Neural Style Transfer, collaborate on projects, and support each other's learning.
Show steps
Show steps
Show steps
- Find like-minded individuals who are also interested in Neural Style Transfer
- Schedule regular study sessions
- Share knowledge, ideas, and resources with each other
Follow a Tutorial on Neural Style Transfer
Show steps
Supplement your theoretical knowledge by following a guided tutorial that provides step-by-step instructions for implementing Neural Style Transfer.
Show steps
Show steps
Show steps
- Locate a comprehensive tutorial that covers the implementation of Neural Style Transfer
- Follow the instructions in the tutorial carefully
- Troubleshoot any issues that may arise during the implementation
Five other activities
Expand to see all activities and additional details
Show all eight activities
Attend a Workshop on Neural Style Transfer
Show steps
Advance your skills by attending a workshop dedicated to Neural Style Transfer, led by experts in the field.
Show steps
Show steps
Show steps
- Research and find workshops on Neural Style Transfer
- Register for a workshop that fits your schedule and interests
- Attend the workshop and actively participate in discussions and activities
Create a Neural Style Transfer Application
Show steps
Reinforce your understanding of Neural Style Transfer by building a simple application that demonstrates the technique's capabilities.
Browse courses on
Neural Style Transfer
Show steps
Show steps
Show steps
- Set up the necessary environment and libraries for developing the application
- Gather a dataset of images to be used for style transfer
- Implement the Neural Style Transfer algorithm
- Evaluate the performance of your application on the dataset
Contribute to Open-Source Projects
Show steps
Gain practical experience and deepen your understanding by contributing to open-source projects related to Neural Style Transfer.
Show steps
Show steps
Show steps
- Identify open-source projects in the field of Neural Style Transfer
- Choose a project that aligns with your skills and interests
- Contribute code, documentation, or other resources to the project
Develop a Neural Style Transfer App
Show steps
Demonstrate your mastery of Neural Style Transfer by creating a fully functional application that incorporates the technique.
Show steps
Show steps
Show steps
- Design the architecture and user interface of your application
- Integrate the Neural Style Transfer algorithm into your application
- Implement features for user interaction and image manipulation
- Test and deploy your application
Participate in a Neural Style Transfer Competition
Show steps
Challenge yourself and test your skills by participating in a competition that focuses on Neural Style Transfer techniques.
Show steps
Show steps
Show steps
- Research and identify competitions that are relevant to Neural Style Transfer
- Develop an innovative approach to Neural Style Transfer
- Submit your work to the competition
Career center
Learners who complete Applications of Computer Vision & Deep Learning will develop knowledge and skills
that may be useful to these careers:
Management Consultant
Management Consultant
Management Consultants help businesses improve their performance. They work on a variety of projects, such as developing new strategies or improving operational efficiency. This course can help a Management Consultant develop skills to build models using deep learning and computer vision techniques. These skills can be used to develop products such as image recognition software or self-driving cars.
Marketing Manager
Marketing Manager
Marketing Managers develop and execute marketing campaigns. They work on a variety of projects, such as developing new marketing strategies or managing social media campaigns. This course can help a Marketing Manager develop skills to build models using deep learning and computer vision techniques. These skills can be used to develop products such as image recognition software or self-driving cars.
Sales Manager
Sales Manager
Sales Managers lead and manage sales teams. They work on a variety of projects, such as developing new sales strategies or managing customer relationships. This course can help a Sales Manager develop skills to build models using deep learning and computer vision techniques. These skills can be used to develop products such as image recognition software or self-driving cars.
Data Scientist
Data Scientist
Data Scientists study large sets of data to find patterns and gain insights. They build models that can make predictions or recommendations. This course can help a Data Scientist develop skills to build models using deep learning and computer vision techniques. These skills can be used to develop products such as image recognition software or self-driving cars.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers design, develop, and deploy machine learning models. They work on a variety of projects, such as building models to detect fraud or predict customer behavior. This course can help a Machine Learning Engineer build skills to develop models using deep learning and computer vision techniques. These skills can be used to develop products such as image recognition software or self-driving cars.
Business Analyst
Business Analyst
Business Analysts use data and analytics to solve business problems. They work on a variety of projects, such as developing new products or improving customer service. This course can help a Business Analyst develop skills to build models using deep learning and computer vision techniques. These skills can be used to develop products such as image recognition software or self-driving cars.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use mathematical and statistical techniques to solve business problems. They work on a variety of projects, such as optimizing supply chains or scheduling production. This course can help an Operations Research Analyst develop skills to build models using deep learning and computer vision techniques. These skills can be used to develop products such as image recognition software or self-driving cars.
Statistician
Statistician
Statisticians use mathematical and statistical techniques to analyze data. They work on a variety of projects, such as designing experiments or conducting surveys. This course can help a Statistician develop skills to build models using deep learning and computer vision techniques. These skills can be used to develop products such as image recognition software or self-driving cars.
Data Analyst
Data Analyst
Data Analysts collect, clean, and analyze data to find patterns and gain insights. They work on a variety of projects, such as analyzing customer data or financial data. This course can help a Data Analyst develop skills to build models using deep learning and computer vision techniques. These skills can be used to develop products such as image recognition software or self-driving cars.
Financial Analyst
Financial Analyst
Financial Analysts analyze financial data and make recommendations. They work on a variety of projects, such as developing investment strategies or analyzing financial statements. This course can help a Financial Analyst develop skills to build models using deep learning and computer vision techniques. These skills can be used to develop products such as image recognition software or self-driving cars.
Product Manager
Product Manager
Product Managers develop and manage products. They work on a variety of projects, such as launching new products or improving existing products. This course can help a Product Manager develop skills to build models using deep learning and computer vision techniques. These skills can be used to develop products such as image recognition software or self-driving cars.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use mathematical and statistical techniques to analyze financial data. They work on a variety of projects, such as developing trading strategies or pricing financial instruments. This course can help a Quantitative Analyst develop skills to build models using deep learning and computer vision techniques. These skills can be used to develop products such as image recognition software or self-driving cars.
Actuary
Actuary
Actuaries use mathematical and statistical techniques to assess risk. They work on a variety of projects, such as pricing insurance policies or developing pension plans. This course can help an Actuary develop skills to build models using deep learning and computer vision techniques. These skills can be used to develop products such as image recognition software or self-driving cars.
Software Developer
Software Developer
Software Developers design, develop, and deploy software applications. They work on a variety of projects, such as building web applications or mobile apps. This course can help a Software Developer develop skills to build models using deep learning and computer vision techniques. These skills can be used to develop products such as image recognition software or self-driving cars.
Computer Vision Engineer
Computer Vision Engineer
Computer Vision Engineers design, develop, and deploy computer vision systems. They work on a variety of projects, such as building systems to detect objects or track people. This course can help a Computer Vision Engineer develop skills to develop models using deep learning and computer vision techniques. These skills can be used to develop products such as image recognition software or self-driving cars.
For more career information including salaries, visit:
OpenCourser.com/course/ga4eo5/applications
Reading list
We've selected five 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
Applications of Computer Vision & Deep Learning.
Save
Provides a comprehensive overview of computer vision algorithms and their applications. It covers a wide range of topics, from image processing and feature extraction to object recognition and tracking. 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 the latest techniques and algorithms for image classification, object detection, and segmentation. It valuable resource for anyone who wants to learn more about deep learning for computer vision.
Provides a comprehensive and up-to-date overview of computer vision. It covers a wide range of topics, from image processing and feature extraction to object recognition and tracking. It valuable resource for anyone who wants to learn more about computer vision.
Save
Provides a comprehensive overview of deep learning. It covers the latest techniques and algorithms for deep learning, and it valuable resource for anyone who wants to learn more about deep learning.
Provides a comprehensive overview of pattern recognition and machine learning. It covers a wide range of topics, from supervised learning and unsupervised learning to Bayesian methods and reinforcement learning. It valuable resource for anyone who wants to learn more about pattern recognition and machine learning.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/ga4eo5/applications
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Time
40 hours
Level
Advanced
Via
Udacity
Instructors
Sebastian Thrun
Cezanne Camacho
Jay Alammar
Alexis Cook
Luis Serrano
Juan Delgado
Ortal Arel
Language
English
Good to know
Develops deep learning skills through practical projects
Taught by industry leaders in deep learning and computer vision
Highly relevant to current industry practices in deep learning and computer vision
Suitable for students with a strong foundation in deep learning and computer vision
Focuses on pre-trained models, which may limit exploration of custom model building
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