Central Limit Theorem In Plain English Naked Data Science podcast

Innehåll tillhandahållet av Naked Data Science. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av Naked Data Science eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.

Naked Data Science »
Central Limit Theorem in Plain English

2y ago 38:44

Dela

MP3•Episod hem

Arkiverad serie ("Inaktivt flöde" status)

When? This feed was archived on February 27, 2024 11:13 (2M ago). Last successful fetch was on March 06, 2024 19:14 (2M ago)

Why? Inaktivt flöde status. Våra servar kunde inte hämta ett giltigt podcast-flöde under en längre period.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

We are trying out a different format in this episode. Nima gave me a topic, which is Central Limit Theorem. I spent an hour learning about it. And then we have a little chat. You will hear why we are doing this in the episode.
And if you like this format, please send us an email at hello [at] nds.show . That helps us decide if we are going to make more episodes like this in the future.
Meanwhile, if you are not a data scientist yet, but want to become one, you should really attend our webinar. We will demystify the transition into data science. We will show you the most effective way to build your skills. And we will advise you on the four possible options you can take to go from where you are to landing a data science job in as little as 9 months. Find out more here.

35 episoder

#Tech #Naked Data Science #Data Science #Data Scientist #Data-driven Innovation #Cross-functional Team #Data Engineering #Machine Learning #Artificial Intelligence