Presentation Title

Applications of Machine Learning in Improving Quality Of Life

Start Date

November 2016

End Date

November 2016

Location

HUB 379

Type of Presentation

Oral Talk

Abstract

This project explores developments in machine learning, a versatile field in computer science involving the construction of algorithms that can learn, that is, develop further capabilities, based on previous datasets in order to make predictions about other data. By applying these ideas to make small tasks more efficient, we can improve the quality of life of everyone. For one, predictive texting allows people to compose text messages more rapidly, saving time and energy. For another, speech-to-text transcribing can especially aid those who may be physically impaired. Finally, the self-driving car, currently in continuing development, has potential to dramatically improve quality of life for the disabled and the general populace. After reviewing research on the technologies involved, 46 survey participants rated their experiences or interest in these technologies. Most respondents indicated that predictive texting was helpful, that speech-to-text was somewhat helpful, and that self-driving cars were helpful. In terms of prospective interest, predictive text had low ratings, speech-to-text transcribing had mixed interest, and the self-driving car had some interest. In conclusion, the project suggests that by utilizing the potential of machine learning, we can create increasingly useful and effective technologies that all people can take advantage of in their everyday lives. The key to future development of this idea is to educate and inform people about the potential uses of machine learning and what benefits these ideas can provide.

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Nov 12th, 2:45 PM Nov 12th, 3:00 PM

Applications of Machine Learning in Improving Quality Of Life

HUB 379

This project explores developments in machine learning, a versatile field in computer science involving the construction of algorithms that can learn, that is, develop further capabilities, based on previous datasets in order to make predictions about other data. By applying these ideas to make small tasks more efficient, we can improve the quality of life of everyone. For one, predictive texting allows people to compose text messages more rapidly, saving time and energy. For another, speech-to-text transcribing can especially aid those who may be physically impaired. Finally, the self-driving car, currently in continuing development, has potential to dramatically improve quality of life for the disabled and the general populace. After reviewing research on the technologies involved, 46 survey participants rated their experiences or interest in these technologies. Most respondents indicated that predictive texting was helpful, that speech-to-text was somewhat helpful, and that self-driving cars were helpful. In terms of prospective interest, predictive text had low ratings, speech-to-text transcribing had mixed interest, and the self-driving car had some interest. In conclusion, the project suggests that by utilizing the potential of machine learning, we can create increasingly useful and effective technologies that all people can take advantage of in their everyday lives. The key to future development of this idea is to educate and inform people about the potential uses of machine learning and what benefits these ideas can provide.