AI and machine learning are two of the biggest buzzwords in the industry right now, but how do you get started using machine learning? How can you identify problems at which machine learning will excel? What tools and libraries are available to be used?
We will use the experience of Teledyne CARIS exploring machine learning for point cloud and imagery data as a case study to show how to get started in this exciting field. We will explore the tools already available in the market as well as cover some basic techniques of machine learning. This will help you understand whether machine learning is the right approach for your problem and how to decide what tools and techniques to try.
We’ll also discuss what needs to be done to train an algorithm and how a trained algorithm can be deployed for use. We’ll present some of the potential pitfalls and stumbling blocks to look out for and lessons we’ve learned as we started our foray into machine learning.
Speaker: Michael Henheffer
Suggested Experience: Any level of development experience should feel comfortable in this session.
Technologies Used: C++, Python, Tensorflow, SVM, PointNet
Keywords: AI, Machine Learning, SVM, Tensorflow, Deep Learning, Neural network