Hello Gopi,
The data frame class project is indeed a good idea, we have thought
about that, but as Ryan said, it can be a big project for GSoC given
the limited period of time this year.
I have several ideas to add on what Ryan said. The objective is to make
the project lighter and more fit for
Thanks for the valuable feedback!
Using the policy-design pattern sounds like a good idea to me, one reason
> why
> we haven't done this for the existing evolution-based optimizers is that
> they slightly
> differ in functionality
>
I was pondering about the same situation. One of the key
Hey Ryan,
Thanks for the feedback.
I agree that this can be a very big project considering the time span of
GSoC this year, if we decide to go ahead with this project it will be very
important to decide on some base features as you already pointed out.
how will users use this dataframe?
We
On Wed, Mar 10, 2021 at 01:25:04AM +0530, Gopi Manohar Tatiraju wrote:
> I am planning to contribute to mlapck under GSoC 2021. Currently, I am
> working on creating a pandas *dataframe-like class* that can be used to
> analyze the datasets in a better way.
>
> Having a class like this would help
Hello Marcus,
I think I didn't make a point very clear in my previous email. Actually
what I found is that there are a couple of libraries like statsmodels and
sktime that are dedicated just for time series forecasting, classification,
regression etc. but I couldn't find any good open source
Hey Marcus,
Yes, you got it correct. We will have a single environment but we can have
multiple agents and reward schemes. I added more info, maybe this will make
things more clear.
These are the building blocks for solving any DRL problem, I tried to keep
it as simple as possible for now, once
