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Extracurricular
Sebastian Thrun,
Thad Starner,
and
Peter Norvig
Sebastian Thrun,
Thad Starner,
and
Peter Norvig
Additional lecture material on hidden Markov models and applications for gesture recognition.
Register for this course and see more details by visiting:
OpenCourser.com/course/rr8l33/extracurricula
What's inside
Syllabus
Thad returns to discuss using Hidden Markov Models for pattern recognition with sequential data.
Thad shares advanced techniques that can improve performance of HMMs recognizing American Sign Language, and more complex HMM models for applications like speech synthesis.
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possible dealbreakers
Taught by researchers who are highly accomplished in work with gesture recognition
Develops techniques for improving performance of Hidden Markov Models for gesture recognition
Examines advanced Hidden Markov Modeling for speech synthesis
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Extracurricular.
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Career center
Learners who complete Extracurricular will develop knowledge and skills
that may be useful to these careers:
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers are responsible for designing, developing, and deploying machine learning models. They use their knowledge of mathematics, statistics, and computer science to build models that can learn from data and make predictions. This course may be useful for Machine Learning Engineers who want to learn more about hidden Markov models and their applications in gesture recognition.
Data Scientist
Data Scientist
Data Scientists use their knowledge of mathematics, statistics, and computer science to extract insights from data. They use these insights to solve business problems and make informed decisions. This course may be useful for Data Scientists who want to learn more about hidden Markov models and their applications in gesture recognition.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use their knowledge of mathematics, statistics, and computer science to solve problems in a variety of industries. They use their skills to improve efficiency and productivity. This course may be useful for Operations Research Analysts who want to learn more about hidden Markov models and their applications in gesture recognition.
Statistician
Statistician
Statisticians collect, analyze, and interpret data. They use their knowledge of statistics to draw conclusions about the world around them. This course may be useful for Statisticians who want to learn more about hidden Markov models and their applications in gesture recognition.
Computer Scientist
Computer Scientist
Computer Scientists conduct research in the field of computer science. They develop new theories and algorithms that can be used to solve problems in a variety of fields. This course may be useful for Computer Scientists who want to learn more about hidden Markov models and their applications in gesture recognition.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. They use their knowledge of computer science to create software that meets the needs of users. This course may be useful for Software Engineers who want to learn more about hidden Markov models and their applications in gesture recognition.
Market Researcher
Market Researcher
Market Researchers collect, analyze, and interpret data about consumer behavior. They use their findings to help businesses develop marketing strategies. This course may be useful for Market Researchers who want to learn more about hidden Markov models and their applications in gesture recognition.
Systems Analyst
Systems Analyst
Systems Analysts use their knowledge of business and technology to design and implement computer systems. They use their skills to ensure that systems meet the needs of users. This course may be useful for Systems Analysts who want to learn more about hidden Markov models and their applications in gesture recognition.
Management Consultant
Management Consultant
Management Consultants use their knowledge of business and technology to help businesses improve their performance. They use their skills to identify problems and develop solutions. This course may be useful for Management Consultants who want to learn more about hidden Markov models and their applications in gesture recognition.
Security Analyst
Security Analyst
Security Analysts use their knowledge of security to protect computer systems and networks from attack. They use their skills to identify vulnerabilities and develop security measures. This course may be useful for Security Analysts who want to learn more about hidden Markov models and their applications in gesture recognition.
Business Analyst
Business Analyst
Business Analysts use their knowledge of business and technology to analyze business processes and identify opportunities for improvement. They use their skills to help businesses make better decisions. This course may be useful for Business Analysts who want to learn more about hidden Markov models and their applications in gesture recognition.
Database Administrator
Database Administrator
Database Administrators use their knowledge of databases to design, implement, and maintain database systems. They use their skills to ensure that databases are reliable and efficient. This course may be useful for Database Administrators who want to learn more about hidden Markov models and their applications in gesture recognition.
Network Administrator
Network Administrator
Network Administrators use their knowledge of networks to design, implement, and maintain computer networks. They use their skills to ensure that networks are reliable and efficient. This course may be useful for Network Administrators who want to learn more about hidden Markov models and their applications in gesture recognition.
Financial Analyst
Financial Analyst
Financial Analysts use their knowledge of mathematics, statistics, and finance to analyze financial data. They use their findings to make investment recommendations and advise clients on financial matters. This course may be useful for Financial Analysts who want to learn more about hidden Markov models and their applications in gesture recognition.
Actuary
Actuary
Actuaries use their knowledge of mathematics, statistics, and finance to assess risk and uncertainty. They use their skills to develop insurance products and advise clients on risk management. This course may be useful for Actuaries who want to learn more about hidden Markov models and their applications in gesture recognition.
For more career information including salaries, visit:
OpenCourser.com/course/rr8l33/extracurricula
Reading list
We've selected ten 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
Extracurricular.
This comprehensive textbook covers a wide range of machine learning topics, including hidden Markov models. It valuable resource for those seeking a broad understanding of machine learning and its applications, including in the context of gesture recognition.
This widely-used textbook provides a comprehensive overview of speech and language processing, including chapters on hidden Markov models and their applications in speech recognition and synthesis.
This classic textbook provides a comprehensive treatment of hidden Markov models. It valuable resource for those seeking a thorough understanding of the theory and applications of HMMs.
This practical guide provides a hands-on introduction to machine learning, including a chapter on hidden Markov models. It valuable resource for those seeking to apply HMMs in real-world applications.
This textbook provides a comprehensive overview of machine learning, including a chapter on hidden Markov models. It valuable resource for those seeking a broad understanding of machine learning and its applications.
This practical guide provides a hands-on introduction to machine learning, including a chapter on hidden Markov models. It valuable resource for those seeking to apply HMMs in real-world applications using popular machine learning libraries.
This textbook provides a comprehensive overview of machine learning, including a chapter on hidden Markov models. It valuable resource for those seeking a broad understanding of machine learning and its applications.
This practical guide provides a hands-on introduction to machine learning, including a chapter on hidden Markov models. It valuable resource for those seeking to apply HMMs in real-world applications.
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This textbook provides a comprehensive overview of data mining, including a chapter on hidden Markov models. It valuable resource for those seeking a broad understanding of data mining and its applications.
This textbook provides a comprehensive overview of machine learning in the R programming language, including a chapter on hidden Markov models. It valuable resource for those seeking to apply HMMs in real-world applications using R.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/rr8l33/extracurricula
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Time
75 hours
Level
Advanced
Via
Udacity
Instructors
Sebastian Thrun
Thad Starner
Peter Norvig
Language
English
Good to know
Taught by researchers who are highly accomplished in work with gesture recognition
Develops techniques for improving performance of Hidden Markov Models for gesture recognition
Examines advanced Hidden Markov Modeling for speech synthesis
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