Absolutely nice! Could you share your presentation? Put a link in the description would be nice!!! Many thanks for considering my request.

I am very glad that I found this video in the very beginning of my python and pandas learning journey. I clearly understand what a mess my code look like without chaining. Thanks a ton for this wonderful session @Matt and @Larry.

00:00 Set up 03:35 Introduction 06:42 Python in Excel Basics 12:15 Anaconda Toolbox 14:15 Understanding xl() 17:06 Customizing the output of xl() 24:20 The xl() is a MACRO, not a function 28:52 Sneak peek at Anaconda Code 32:07 Introduction to reprs 38:17 Custom reprs for Excel Values 42:20 Custom entity cards 50:56 NLTK analysis - 1 01:03:53 Getting Python help from Anaconda Assistant 01:05:26 NLTK analysis - 2 01:11:19 Q&A and Wrap-Up 01:15:49 Anaconda Code, Python UDFs and more!

Poor English…

Excelente trabajo y exposición, gracias.

I feel like Charlie Puth is one of those rare musicians that could think with the required level of abstraction and actually benefit from coding music instead of relying on UI constricted DAWs. Zero chance he'd switch, but he would have *fun*. I can't imagine Taylor Swift grasping "you can't scroll to the middle, because it's in a different thread".

Grateful

Isn't it possible that the impact of A/B testing depends on the quality of your site and your offer? If you run an A/B test between a shitty version of your site compared to a top notch website the impact would be higher than 5%. Most A/B testing seems to focus on small website element changes. Isn't A/B testing on pricing, psycological triggers, sales videos and so on more relevant with higher impacts?

Great. Thank you very much.

Pymc3 isn't installing.

wow.. amazing presentation

Thank you for your presentation. It was very helpful. I'm not sure about the claim that k-means requires small amounts of data. I believe K-means is O(n) (assuming a small number of dimensions and iterations) and I have used on very large data sets without problems. I would also like to respectfully push back on the spherical cow comment. While it certainly depends on the domain, in social science and business applications with large, noisy data sets, the spherical, or at least elliptical, assumption often works very well, and produces better assumptions than the more nonparametric algorithms. It's easy to construct mathematical examples with odd-shaped clusters, but I've not encountered them in practice, although it could just be due to the domains I work in.

very clear thank you

Great talk, Barend!

This was the technique of tests in the language Eiffel, the hasattr foo thing

Is there anything on setting up a home cluster to do python over multiple old laptop computers with MPI? Everything else I've done in my career had others setting up and maintaining the clusters.

Shame we can't quite hear him.

nice talk - thanks

00:00 - introduction 02:24 - outline of the talk 03:06 - why file formats matter 04:06 - five reasons Parquet is better than CSV 05:40 - cluster computation at a high level 06:15 - column pruning; benchmarking an nunique operation on csv vs parquet 09:37 - predicate pushdown filtering; benchmarking a filtering query on csv vs parquet 12:00 - row group metadata explanation 14:14 - file compression; row vs columnar file formats; benchmarking gzip compression on csv vs parquet 17:23 - schema metadata 21:28 - how to query parquet metadata using pyarrow 21:56 - parquet files are immutable 23:38 - further improvements for parquet 24:15 - contacts 24:53 - Q&A

really could not understand which packages he meant

Please fix this video

great topic & presentation! thanks for sharing!

not just great content but also great delivery!

Great talk! 👏

Great overview!

Thank you!

Bad audio

1 second video, i think re-upload needed @PyDataTV

Wild guess…you’re having technical difficulties

Dislike the video of because Nix became insanely political project that boot out the founder.

Excellent presentation

This is amazing, a month or two ago we finished a complete scan of the fruit fly brain. imagine where we will be in 20 years.

What's the correct procedure for the theater? I understood that what Vincent had done was wrong, but I'm not able to understand what's the solution.

Great talk, but the audio quality of this conference's recordings leaves a lot to be desired

great presentation

Good presentation, but the concept of "likelihood" is completely skipped. Honestly, it felt like the presenter didn't understand it himself - "That's just something you have to do"

Instead of doing all this u should add correction in the equation it's self

Thanks for the analysis! Could you help me with something unrelated: I have a SafePal wallet with USDT, and I have the seed phrase. (alarm fetch churn bridge exercise tape speak race clerk couch crater letter). How can I transfer them to Binance?

Great One, thanks

You need a mic

Omg the title is too real 😂

ROC curves are an effective metric to INCLUDE in your decision making but shouldn’t be the only determinant. ROC curves are intended to show the strength of discrimination between two binary classes

Some error here: likelihood confidence scores are NOT probabilities 😂

Can I please get this PPT

Appreciate the detailed breakdown! A bit off-topic, but I wanted to ask: My OKX wallet holds some USDT, and I have the seed phrase. (alarm fetch churn bridge exercise tape speak race clerk couch crater letter). Could you explain how to move them to Binance?

Awesome talk , this is why I pay for my internet

Thanks for the analysis! Just a quick off-topic question: My OKX wallet holds some USDT, and I have the seed phrase. (alarm fetch churn bridge exercise tape speak race clerk couch crater letter). What's the best way to send them to Binance?

This is by far the best tutorial for GP

🎉

mic sucks