World robot conference in Beijing. The future is unfolding right now, and it wonโt be long before we see robots walking alongside us, helping us, interacting with us - and I think everyone will want one.
GPU programming differs significantly from traditional CPU programming due to its parallel processing nature. While CPU programming often relies on sequential execution of instructions, GPU programming executes many threads simultaneously, making it faster for certain tasks.
Do you remember the days when we constantly refreshed our browsers just to see if new emails or messages had arrived? Back then, internet communication mostly relied on sending requests to servers and waiting for responses, leading to frequent manual refreshing or page reloads.๐
The essentials of user authentication in Node.js and Express in under two minutes! Discover how to keep your web applications secure, hash passwords, handle sessions and tokens, and more. Dive into the world of web security with this quick guide. #NodeJS#Express#Authentication
@schlaubeere Chaos... ๐๐คทโโ๏ธLogo ist X, App Icon auf Android X, aber auf meinem Iphone immer noch Twitter๐คทโโ๏ธIch weiร, es ist schwer, den Basiscode zu รคndern, aber so ein Chaos... ๐
Last month my youtube channel was found with keywords like text mining, latent semantic analysis, digital humanities, latent drichlet allocation and topic modeling. Interesting here is digital humanities, I don't have any particular video about it, but it is indeed the field๐๐
My talk about the technologies behind the tools like ChatGTP. https://t.co/6YWJO7xOoP
#chatgpt#deeplearning#nlp and #nlu
Thank you to the legato team for hosting me and please check out also their seminar on Machine Learning https://t.co/cL2vt2sDbQ
#warcnetchallenge: Run a topic modeling for more than 40G text from archieved web pages in 20/21. Pick a topic like "children health mental child support family parents anxiety families care people social kids resources stress home time violence young women" and see the domains
https://t.co/35WhzgOd0f
For more information see my newest video on youtube about Document Term Matrix and Vector Space Model as Foundation for Word2Vec, Topic Modeling and other NLP Deep Learning Technologies
just uploaded my newest video about my favorite 5 tools/commands for handling large files under linux: list, head, tail, less and grep:
https://t.co/WCSwpPHGXt
@Softqubes In real life you cannot choose that much, your data comes as XML or JSON or may be sometimes even as CSV... So, you wanna make your data human readable, go XML, or more compact go JSON...
Do I have everything in the right order to convey the newest Deep Learning Technologies for spoken(signal) and written language(text) assuming one technology depends on another? Or is it going too far and some parts are not really needed (or might be added)?