What data transformation library should I use? Pandas vs Dask vs Ray vs Modin vs Rapids (Ep. 112)| Listen on Anghami

Mar 6

Programmable Money: The Cage They'll Call Convenience (Ep. 300)

Money has always been yours to spend freely. That's about to change. This episode breaks down programmable money, the technology that turns your wallet into a permission system. ✨ Connect with us! Personal newsletter: https://defragzone.substack.com 📩 Newsletter: https://datasci ... Show More

24m 37s

Mar 3

There Is No AI. There's a Stateless Function on 10,000 GPUs Pretending to Know You (Ep. 299)

Right now, millions of people are simultaneously chatting with a system that remembers nothing, knows nothing, and resets after every message. The engineering keeping that illusion alive is actually the impressive part. ✨ Connect with us! Personal newsletter: https://defragzone.s ... Show More

39m 29s

Jan 30

Your Favorite AI Startup is Probably Bullshit (Ep. 298) [RB]

The brutal truth about why Silicon Valley is blowing billions on glorified autocomplete while pretending it's the next iPhone. We're diving deep into the AI investment circus where VCs who can't code are funding companies that barely understand their own technology. From blockcha ... Show More

12m 20s

Sep 2021

Massively Parallel Data Processing In Python Without The Effort Using Bodo

<div class="wp-block-jetpack-markdown"><h2>Summary</h2> <p>Python has beome the de facto language for working with data. That has brought with it a number of challenges having to do with the speed and scalability of working with large volumes of information.There have been many ... Show More

1h 4m

Mar 2024

#454: Data Pipelines with Dagster

See the full show notes for this episode on the website at <a href="https://talkpython.fm/454">talkpython.fm/454</a>

58m 25s

Nov 2022

Analyze Massive Data At Interactive Speeds With The Power Of Bitmaps Using FeatureBase

<div class="wp-block-jetpack-markdown"><h2>Summary</h2> <p>The most expensive part of working with massive data sets is the work of retrieving and processing the files that contain the raw information. FeatureBase (formerly Pilosa) avoids that overhead by converting the data int ... Show More

59m 25s

Dec 2019

Building The Materialize Engine For Interactive Streaming Analytics In SQL

<div class="wp-block-jetpack-markdown"><h2>Summary</h2> <p>Transactional databases used in applications are optimized for fast reads and writes with relatively simple queries on a small number of records. Data warehouses are optimized for batched writes and complex analytical qu ... Show More

48m 7s

Jul 2023

#422: How data scientists use Python

See the full show notes for this episode on the website at <a href="https://talkpython.fm/422">talkpython.fm/422</a>

1h 2m

Sep 2022

#382: Apache Superset: Modern Data Exploration Platform

See the full show notes for this episode on the website at <a href="https://talkpython.fm/382">talkpython.fm/382</a>

1h 8m

Nov 2021

Exploring Processing Patterns For Streaming Data Integration In Your Data Lake

<div class="wp-block-jetpack-markdown"><h2>Summary</h2> <p>One of the perennial challenges posed by data lakes is how to keep them up to date as new data is collected. With the improvements in streaming engines it is now possible to perform all of your data integration in near r ... Show More

52m 53s

Aug 2023

#425: Memray: The endgame Python memory profiler

See the full show notes for this episode on the website at <a href="https://talkpython.fm/425">talkpython.fm/425</a>

1h 10m

Oct 2023

Reducing The Barrier To Entry For Building Stream Processing Applications With Decodable

<h2>Summary</h2> <p>Building streaming applications has gotten substantially easier over the past several years. Despite this, it is still operationally challenging to deploy and maintain your own stream processing infrastructure. Decodable was built with a mission of eliminat ... Show More

1h 8m

What data transformation library should ...