autokad

78 ms·

871.
by autokad 8y ago
wouldn't be surprised if they went to something that was unusable after 3 years and said 'its for the environment'
872.
by autokad 8y ago
I was kinda hoping for: "I should stop acting like an 8 year old child" moment, but I suppose that's not happening yet. was hoping for any of the following: businesses are made up of people. no one group of people are bette
873.
by autokad 8y ago
I remember about 5 years ago when all my classmates were gaga over joining start ups. I was like why in the world? - The chances of failure is really high - The pay is lower than big tech - The hours are longer than big tech - you bust
874.
by autokad 8y ago
thanks for more eloquently wording what I was trying to say
875.
by autokad 8y ago
I'm not talking about that, but if they don't want you visiting, they sure as heck don't want you staying.
876.
by autokad 8y ago
does anyone notice how if other people say something along the lines of: 'we need to stop outsiders from coming here' it gets explained away as something like 'altering the character of historic cities' whereas if an ame
877.
by autokad 8y ago
I doubt it is, but I also don't fault someone for thinking so. Einstein showed up after 3 scrolls. For me, "there are literally zero black", was not true. predominately not black, but Washington was in the list. I don&#x27
878.
by autokad 8y ago
by "overrepresentation of black scientists", in my case it means 100%.
879.
by autokad 8y ago
i personally dislike them, they are rats with wings imo they bread like crazy and shit on everything. I didn't take much notice when a pair nested under my deck. it wasn't long before two became 10+. It was really difficult to
880.
by autokad 8y ago
if you really understand ML/DS, then you would know that ML is founded on all the same concepts. > "... they tackle data is radically different from statistician ..." the short answer is, before we had limited data, comput
881.
by autokad 8y ago
> "he 30% cut they ask of developers is more than reasonable." Not really, the fee's much of big tech often puts on people are draconian, and they are able to continue doing so because of the monopolies they hold. 30% is
882.
by autokad 8y ago
keep trying, especially other companies
883.
by autokad 8y ago
i use it to denote a lasting sound. like heeey = hey~
884.
by autokad 8y ago
I guess its subjective by what they mean by "the Internet has less than half as much data". I imagine what existed on file sharing sites was more (if that counts). As of 2007, I had 1 TB of specific types of content, which would
885.
by autokad 8y ago
I don't find it odd or wrong that companies are abiding to the law when they offer services within a certain jurisdiction. Google pulled out because of hacking and attacks against their services, if I remember correctly.
886.
by autokad 8y ago
I am willing to bet once you account for other things, such as geography, the effect goes away. Look at the map at the end. It clearly shows women being higher percentage in areas that have better mortality rates for heart disease which ar
887.
by autokad 8y ago
as others pointed out, it cant be really used for anything else. I'll also add to that, look how much of the rocky mountains was listed as 'pasture / range'
888.
by autokad 8y ago
I am not 100% this is true. people want things narrowed down to as little text as possible, consider the fact that many people read headlines and stop there. when talking to a writer i knew, he would always do this type of dress up with st
889.
by autokad 8y ago
I think it just followed tech on a strong upward pace. Perhaps ETFs pulled it along for the ride
890.
by autokad 8y ago
if we continued to live as 'chimps' as some have worded it, the chances of extinction for humans, and all life on this planet is 100%. for all the damage done to ecological systems, now the chances of humans and some of those syst
891.
by autokad 8y ago
well, I certainly think pluto is more of a planet than these are moons
892.
by autokad 8y ago
new person to amazon. they have a lot of really amazing and smart people. but like anything in life, its what you make of it. I'd say put your best into the position and try to learn as much as you can from others. no good reason to
893.
by autokad 8y ago
alzheimers is probably like cancer. its not useful to talk about 'one cure' when in reality its many diseases. in alzheimer's case, its probably a symptom of many possible things that can go wrong
894.
by autokad 8y ago
Sheets are surprisingly hard to buy. The best sheets I have ever bought were 300 count from IKEA. I swear to god they feel like a much higher thread count
895.
by autokad 8y ago
nice article, there is a kaggle competition (Spooky Author) that you had to identify which of three authors wrote a sentence. the problem is very much the same, so not only can you try your technique on the data, you can also read kernels
896.
by autokad 8y ago
interesting read. I liked the part about identifying rare templates. plus, if I ever plan to do ML on html the article gave me a good place to start on feature extraction. might have some uses in identifying phishing urls, etc
897.
by autokad 8y ago
do they? in the article 136k w/ 4-6 yrs exp really isn't a lot, especially since it has a higher % of PHDs. i became a data scientist because I love that type of work. I like solving puzzles and diving deep into data and helping
898.
by autokad 8y ago
I think its going to be like websites/internet back in the early 2000s. Everyone knew it was the future, but didn't know what to make of it. Many did it wrong and the profits (if there were any) didn't live up to expectatio
899.
by autokad 8y ago
usually I am joining many different data sets many of which include some time of log data (sometimes petabytes in size but usually a few TB). the logs are persisted to hdfs or s3, which is why spark and hive make such a nice way of doing w
900.
by autokad 8y ago
psudocode here: yhat_xgboost = xg.predict(x_test) y_hat_cat = cat.predict(x_test) y_hat = .7 * y_hat_xgboost + .3 * y_hat_cat how is that not little effort?

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