All are welcome, what seems to be in short supply is stuff at either end, the fundamentals and what a master student might encounter.
To briefly explain why I'm asking this, and why the answers may be of value to others in this community:
I'm trying to break into AI, to understand a large amount of the theory you effectively have to be well versed in statistics. I come from an engineering background where it's really more understanding abstract concepts at speed and applying them correctly with frameworks. While I understand a lot can be achieved by going through projects in TensorFlow and doing some Googling, I feel like I don't understand the internals. Thanks for taking the time to read this.
To briefly explain why I'm asking this, and why the answers may be of value to others in this community:
I'm trying to break into AI, to understand a large amount of the theory you effectively have to be well versed in statistics. I come from an engineering background where it's really more understanding abstract concepts at speed and applying them correctly with frameworks. While I understand a lot can be achieved by going through projects in TensorFlow and doing some Googling, I feel like I don't understand the internals. Thanks for taking the time to read this.