#Sizewise neenah how to#

It's probably best known for being the home of the Road America Racetrack, which is said to slang a good charcoal kissed burgers on raceday.

Elkhart Lake is a small village located on the beautiful Kettle Moraine Scenic Drive. I was out in Sheboygan County on a consulting trip a little while back and seeked out a couple good burger stops on my route. (edited to correct the denotation of Butterburger®) Dangerous that this chain is on most of my well traveled routes around the midwest! Curds were noticeably better than our first attempt as well. Though as evidenced by the unmelted cheese, the toppings were not managed quite up to my gold standard. I love a crispy, lacy griddled burger and this is a pretty good one, almost up there with my favorite, Schoop's. On the ride home from up dere, my wife insisted we stop at Culver's for my first Butterburger®. My side, gravy fries, though likely produced from industrial products, hit the spot and with crisp fries and piping hot gravy were more than a sum of their parts. I think we ordered pretty light, a 'large' burger each (maybe 3 oz.?) and a side each. Every thing seems sized and priced to scale up or down the size of the meal. We appreciated the restrained portion sizes though. My better half ordered the cheese curds, which seemed to be a mass-produced product. The bun was well managed on the grill as well, which allowed for the cheese and butter schmear to coalesce into gooey/greasy perfection. Being of the griddled/ slider disposition, this style really did the trick for me. Like Da Beef discusses upthread, these burgers begin as balls of ground that are smashed onto the griddle with onions. Yes, of the butter burger on a kaiser variety like Mickey-Lu's, where I was not completely wowed on my last trek north. We bellied up to the counter for a good view of the grill man in action.Ī great little burger.

This place is the real deal, a cute-as-a-button lunch counter filled with locals (no stares, all smiles). Munising seemed like a good halfway stop and Bud Wilman's was an easy on/off from 43. Well, I ended up doing my homework on the thread and was very glad I did. One day I will sort all these out on google maps for all to be able to use. But if you didnt love Mickey Lu that's the way most places along the lake make them so keep that in mind. The brat burgers in Sheboygan wouldn't be a bad choice either. Al's burgers are the same smashed style as Kewpee and they make a mean hash. I'd heard Al's Hamburger in Green Bay is back at it after a fire so they're there too. I'd say Kroll's East in Green Bay featured upthread is a good option. Well Kewpee does open early so that option should be there. Though an old school roadside haunt would be ideal. I'd love to try something new though, even in Milwaukee, where I've sadly not explored as much as I should. I love Kewpie (and the griddled style in general) so a late breakfast in Racine could be in the cards. Can I get some recommendations on a great burger along the way that won't put us more than 10 miles off track? Last year I hit Mickey Lu's in Marinette and thought it was okay, charming, but not my favorite burger. Tomorrow we head up to Marquette via the typical route of 94 to Milwaukee, then 43 to Green Bay, and 41 to Marinette/ Iron Mtn. So pardon my laziness to not google map each of these small town joints to figure out which might be on the way for us on our next trip up north. Recall that the squared Euclidean distance between any two vectors a and b is simply the sum of the square component-wise differences.Jefe wrote:I am a big fan of this thread, but only vicariously, since I maybe make it up to WI once a year and usually en route to da UP. Also be sure that you have the Numpy package installed. If you are interested in following along, fire up iPython in a terminal session (or create a new Jupyter Notebook).

#Sizewise neenah how to#

Here, we will briefly go over how to implement a function in python that can be used to efficiently compute the pairwise distances for a set/or sets of vectors. In machine learning they are used for tasks like hierarchical clustering of phylogenic trees (looking at genetic ancestry) and in natural language processing (NLP) models for exploring the relationships between words (with word embeddings like Word2Vec, GloVe, fastText, etc.). Distance matrices are a really useful data structure that store pairwise information about how vectors from a dataset relate to one another.