Feeling_Card_4162
Feeling_Card_4162 t1_j7v0c5a wrote
Reply to comment by LeadershipComplex958 in Taking a ML Grad class without any ML experience? [D] by LeadershipComplex958
Wouldn’t know. That was back in 2012 so they only offered the one class at my school. It would make sense to me though that the ML side is more math heavy
Feeling_Card_4162 t1_j7uyqsa wrote
I took a graduate AI class with a similar curriculum in undergrad and did great with it. I think you’ll do fine if you’re good with math.
Feeling_Card_4162 t1_j7kp7rq wrote
Reply to comment by dfcHeadChair in [D] What techniques can I use to tell if a problem is likely enough to be solved by ML so as to justify compiling the dataset? by SnuggleWuggleSleep
This is a good way to get an idea of the financial benefit but it’s also important to think about the knowledge you’ll gain and how much other people would benefit from it when deciding whether to continue or not. There is more to determining if something is worth your time than just money.
Feeling_Card_4162 t1_j792r6d wrote
Reply to 15 years old and bad at math [D] by Daniel_C_____
There’s also the option of doing something like www.code.org/ai. Code.org is a good and free self-teaching curriculum. We use it at the high school I volunteer to help teaching.
Feeling_Card_4162 OP t1_j77oir0 wrote
Reply to comment by dancingnightly in [R] Topologically evolving new self-modifying multi-task learning algorithms by Feeling_Card_4162
Is that the mixture of experts sparsity method? I’ve looked into that a little bit before. It was an interesting and useful design for improving representational capacity but still imposes very specific constraints on the type of sparsity mechanisms available and thus limits the potential improvements to the design. I haven’t heard about the GeNN library. It sounds useful though, especially for theoretical understanding. I’ll check it out. Thanks for the suggestion 😊
Feeling_Card_4162 OP t1_j74gohh wrote
Reply to comment by ID4gotten in [R] Topologically evolving new self-modifying multi-task learning algorithms by Feeling_Card_4162
The point is to be more efficient and dynamic than a normal FF network w/ backpropagation
Feeling_Card_4162 OP t1_j744rzv wrote
Reply to comment by blimpyway in [R] Topologically evolving new self-modifying multi-task learning algorithms by Feeling_Card_4162
As I stated, either a combined score over a set of tasks or abstracted away by using rtNEAT. In the case of rtNEAT, it would be up to the agent when to reproduce depending on the provided dangers, etc. in the simulated environment
Feeling_Card_4162 OP t1_j742xzl wrote
Reply to comment by blimpyway in [R] Topologically evolving new self-modifying multi-task learning algorithms by Feeling_Card_4162
Sorry I don't think I understand your question.
Submitted by Feeling_Card_4162 t3_10sw0q1 in MachineLearning
Feeling_Card_4162 t1_j8a1w08 wrote
Reply to comment by KarmaQueenOfficial in [D] Simple Questions Thread by AutoModerator
Honestly, YouTube is a good resource when combined with reading academic papers