hey today studying to ml algos start as of now ->

yep -> so the situation is -> yep I funnily still had not finished the remnant chapters of Lawvere book. and currently wish to finish.  :) 

yep the thing is -> currently e.g. chapter of -> e.g. the behaviour of monics and epics under the contravariant functoriality of exponentiation seems kind of not the most interesting to study. yep so reason of adhd cause. but its required to learn this chapter also. 

yep time to get over adhd and continue studying this book and finish it during today and then switch to topos book readings.  to then resume the very first NLP translation task (yep there are countless such tasks, but the hmm data engineering type of task of this first task (not the topoi theoretic complexity but data engineering challenge)  is kind of challenge but i think the nonbatch option would wishfully would alleviate the 22billion record issue well in local computer kubernetes stuff. so first NLP task among countless many, is not NLP side wise the most challenging but rather data engineering wise were challenging. but other NLP tasks are topos representation wise challenges, not very hard to solve design engineering  challenges but still challenging some. 

-> unfortunate :S -> there is no exercises answer book for Sets for Mathematics book of Lawvere.  wished there existed :) (since there are some interesting queries in exercises that I wished to not spare time to solve but read how its solved.  )  

yep with lots of adhd i am iterating this chapter consequences and use of exponentials. 

We came to an interesting abstraction of the general fourier transform process. (interesting! )

but then furtherly we came to distributive law conceptualization which is less interesting currently. 

I think but furthermore, the next chapter is actually having more interesting discussions like integrals transforms and metric functions discussions (an abstract tangent to measure theory topics) 

but the other following chapter is more interesting. if only I had less adhd :)

but even with adhd alot, yep trying my best to iterate. 

today have alot adhd since paused alot project recently last days which removed focus mode to reading/studying to lazy mode and I think but wishfully would fix this focus issue today.  everytime i give some pause, i lose focus capability during reading/studying and alot adhd happens. but nevertheless its important to finish these chapters asap. 

hmm the generalizations and deductions based on such abstractions were a topic I were already wondering myself when studying representation theory (I mean for posets and monoids etc) and here we are we see such queries are analyzed very well by Lawvere in following some last chapters of this book. 

I mean I were also interested to do such comparative grp representations which do not exactly map but which still partially represent and we could have some inferences on their poset structure. (e.g. partially-similarity from one grp to other alike etc i mean not fully same similarity but translation between which does not lose some structure based on to some modulo there and then our inference capability to the partial-similarity having grp's algebra  is one topic that I got curious to when reading representation theory. and here we are, we see such poset wise inferences and so are seemingly already analyzed and done by Lawvere. it were like when checking topics in following chapters, I became like -> aha! I were wondering about this or such queries when studying to representation theory.  so found some already done thought process and analysis by in following chapters of this book. 

so even if this chapters create alot adhd currently, i think its even with lots adhd very important to iterate.

but i think i might skip somewhat proof of distributive law topics of bijection construct there since currently thats not interesting.

all a while i been interested to integral topics and seeing following chapter starts very nice analysis based on this functorial analysis methods for such domain which I am eager to come to such chapter asap.  since i had not had very much time to study to measure theory yet only some fundemantals of mt readings but definitely had not learnt yet. plus speculating about integral types is always an interesting topic.  

yep as my curiosity to msc math queries started with integral related queries. and such alike. Its quite interesting to come to following chapter soon to read about analysis of such functors. 

hmm yep. this second part of this book I wish i could finish today (currently at mid of chapter 7).

hmm. I think its like last chapters of this book are answers to queries I wondered when reading representation theory. of from 0.1 version of ml algos to 1.0 version development, I would as mentioned write some skills and those skills were having among this restricted representation theory wise (non generic functor) wise connected graphs algebraic structure inferences alike topics I very wondered. then here we are, we see Lawvere already analysis such queries in i think last chapter. As I curiously checked chapters to see whats coming in following chapters. 

Quite nice! this were a topic i wished to have write a skill set to ml algos 1.0 version. and here we are we see basics of such inference methods already raised/analyzed by Lawvere at last chapters of the book. 

nice!

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Even if i got over for today indefinite adhd mode,  still -> distribute law isomorphism proof section-> you are too uninteresting section from this chapter so even without main adhd issue, i would skip this section of this chapter since its too much uninteresting:S even reading proof of isomorphisms there, indefinitely uninteresting. 

but then other section says Cantor's diagonal Argument. yep seems already an interesting section. definitely wouldnt skip. 

yep Cantor's diagonal argument section of chapter (ending section of this chapter) turned out really most interesting on quantifying infinity with fixed point method.