Good evening, everyone. Please feel free to share your questions in the chat.

Can we get a copy of this document?

I'll verify with the speaker that he's ok with sharing.

What are the next steps after learning libraries like tenserflow?

Learning Tensorflow is a very small piece of becoming a data scientist, and many data scientists go years (or more) without using Tensorflow. In fact, most "real-world" projects require a lot of analysis and manual effort before even considering using a neural network to solve a problem.

This is an example of a project which actually required very little, if any, machine learning. This was more about data analysis, forecasting and data visualization for sharing results.

The Fourier transform is an advanced concept which requires understanding of calculus and linear algebra, specifically an understanding of series representations of functions.

Can the Fourier transform formula ∫f(x) * e^(-2πixξ) dx be used with any function, or is it specifically a periodic function?

It is primarily used for periodic functions.

Thanks

Was this one of the most complicated machine learning projects you have done?

The Flight Decoder

I'll ask during the Q&A!

How important was the background to do the stats and the machine learning algorithms.

When you say "background", do you mean the subject matter expertise? That is, understanding the aircraft and their instrumentation?

Yes

I'll pose that to Dr. Stockton during the Q&A as well. In general, this is a VERY important part of data science projects. In general, the data scientist isn't an expert in the subject matter for every project they take on and require partnerships with other individuals to thoroughly understand the problem, the data and the results.

How much is your work and research be used for future plans in the industry?

I'll ask during the Q&A!

How is IoT sensor data collected in that large of a scale in a timely and efficient manner?

Thank you so much! :)

Thank you so much!

Thank you so much!!!

Thank you Dr. Stockton