Hi there everyone!

As the title says, hi there everyone!

A couple of you will have met me by now from the recent sessions, but if not, my name is Liam! I’m a work colleague of Will’s, and my background comes from my Maths degree and work as a document developer. I’m most comfortable in C#, but I have a little bit of experience in other languages too.

I’m excited to be able to get out of the house for a change, and learn about all things tech related! I’m particularly interested in helping out with projects, improving my programming capabilities, and learning to solder!

I’m happy to help out in any way that I can, so feel free to get in touch!

Welcome to Tech Shed and to the forum!

Nice to have you on board Snowy. Do you ski by any chance?

Thanks very much! I’m afraid I’ve never skied in my life though!

@Snowy Reference our Conversation about Maths on Wednesday and different topics; I am wondering if anyone would be interested in working out run-time complexity using BigO and the other metrics that are used in analysing algorithms and also the maths behind some ML stuff like Neural Networks (linear algebra)?

(I too have a maths background, and can spot a quadratic algorithm by the simple expedient of measuring it twice! Perhaps that’s the engineer in me.)

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I don’t have a maths background [software dev], but have been through a bunch of the ML maths [linear regression/matrices, back-prop etc.] and want to keep learning/firming up that knowledge and putting it to use where I can.
(managed to pass courses on it, but haven’t been using it so I fear it might get lost - a lot of practical ML is abstracted away from the raw maths)

I must admit that I don’t have a great deal of familiarity in either topic, but I would like to learn about Machine Learning in general. My best friend from uni, however, has studied and practiced machine learning as part of his job, so I could refer to him for guidance!

Sweet, maybe we could use the sensor data as training data for some ML models?

If anyone’s interested, I’ve started an ML thread aimed at capturing stuff people are learning or trying out.