Applications Of Machine Learning 2024 / edited by Michael E. Zelinski [and four others].

Format:

Book

Contributor:

Zelinski, Michael E., editor.

Language:

English

Subjects (All):

Machine learning--Congresses.

Machine learning.

Artificial intelligence--Congresses.

Artificial intelligence.

Physical Description:

1 online resource

Place of Publication:

California, United States : SPIE, 2024.

Summary:

Machine learning is one of the most exciting technologies that one would have ever come across. As is evident from the name, it gives the computer that which makes it more similar to humans: The ability to learn. Machine learning is actively being used today, perhaps in many more places than one would expect. -- Today, companies are using Machine Learning to improve business decisions, increase productivity, detect disease, forecast weather, and do many more things. With the exponential growth of technology, we not only need better tools to understand the data we currently have, but we also need to prepare ourselves for the data we will have. To achieve this goal we need to build intelligent machines. We can write a program to do simple things. But most of the time, Hardwiring Intelligence in it is difficult. The best way to do it is to have some way for machines to learn things themselves. A mechanism for learning - if a machine can learn from input then it does the hard work for us. This is where Machine Learning comes into action. Some of the most common examples are: -- Image Recognition -- Speech Recognition -- Recommender Systems -- Fraud Detection -- Self Driving Cars -- Medical Diagnosis -- Stock Market Trading -- Virtual Try On.

Contents:

Front Matter: Volume 13138 (1)

Healthcare and Biomedical Applications (5)

Environmental Applications (4)

Industry, New Methods, and Science Applications I (4)

Industry, New Methods, and Science Applications II (4)

Industry, New Methods, and Science Applications III (3)

Industry, New Methods, and Science Applications IV (4)

Poster Session (8).

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

1-5106-7937-5