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Watching in 2024

I'm invading Shanghai 🎉

discontinued :(

Excelent

NJ😮

Thank you for this video what about spacy instead of stanford? did you try it?

the answers to almost all my questions on the topic are given in 26 min video. Awesome!

Great work Sameer, the depth and clarity which you explain is just outstanding. Could you please help me with the PPTs url, i am not able to find it in link attached in description.

Can I get to know the design of your reward function? And when bidding for 24 hours, how do you make sure that which actions are best to take and how did you model the problem?

A good analysis.

She says it, folks. Whatever handful of women stay in “tech” pursue “feminine” positions. The speaker is in Marketing, Sharon heads the Customer Success department, Maddy takes over Product Management and Val leads the Design team. Just because the company is tech doesn’t mean it’s stem. The speaker explains nothing really of the reasons why 1) many women leave STEM fields and 2) the women who stay choose “feminine” positions

Me encanta su estilo ella es hermosa.

Good

Hi, by any chance has anyone made notes for this lecture?

This is pathetic!

Great talk and explanation of the Tdigest algorithm as well as Erik's excellent implementation of the same. ASCII plots were unexpected and impressive :D

_

Excellent. Best wishes.

and now we have chatGPT

really wonderful talk!

damn 5 years ago...i absolutely loved the presentation engaging is a difficult job..u did great also is it me or anyone else..these 2 faces looks too familiar by the time video ends

good

excellent. it would definitely gonna help. it would great if you could share sqlVis_ggplot_raster wrappers

my head = 1min.:D

this still a relevant video? thanks

Still waiting for streaming Random Forest (

Great session, well presented. In QA session the query on groupByKey, is a valid one. For immutable types like string using groupByKey over reduceByKey is preferred.

Hii.. this is one of the best presentation about spark. One question is, Spark evolved a lot from here. Are these concepts still relevant till today? Any changes or obsolete content of this video? Can any one tell me pls.

Thank you this is very helpful!

This is one of the best free videos ever available on the youtube community.

Just want to share. I came across this video back in 2016 when spark was a buzz word mostly. Did not understand most of it back then and did not watch it. Now again watching it in 2022. It's true gem.

Kandungan video sangat baik, tahniah

Great presentation , the croud is like shit no support nothing

Thanks for superbly breaking down the mistakes and their solutions. Thanks for the excellent presentation.

LESGOOOOO KENT!

min 9 it starts talking about best practices

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I say Ban "Megzie Ssyk"!

that was an amazing explanation!

Nice video

Where can I get these slides?? Thanks in advance

This presentation is not about fraud prevention. As an audience member said, the title is a fraud. 👎

audio level is very low

good explanations , this would be great if some git code they can mention

debugged a problem by following steps as you explained. Thank you very much. (2022 april)

this is wonderful, enjoyed start to end :)

Great talk sir, you have cleared topics

One of the best videos to learn about Spark Structured Streaming. Watched this once, back in the end of 2020...still relevant.

Could you please demonstrate how to retain decimal value when we write the data frame in json format. Eg : one of my column in df has a value of 12.00 when I write this df into a json file df.write.json(“user/my path/“) . The json file written in this path will have “column”:12.0 instead of 12.00.

Is there a code available for this ??