talk-data.com

Venue: Riverbank House, 2 Swan Ln, London EC4R 3AD

Please note:

1. 🚨🚨🚨A valid photo ID is required by building security. 🚨🚨🚨
2. This event follows the NumFOCUS Code of Conduct. Please familiarise yourself with it before attending.

If your RSVP status says "You're going" you will be able to get in. No need to show your RSVP confirmation when signing in. If you can no longer make it, please unRSVP as soon as possible. *** Code of Conduct: This event follows the NumFOCUS Code of Conduct. Please get in touch with the organisers with any questions or concerns. *** As always, there will be free food and drinks, generously provided by our host, Man Group. ***

⚡ Lightning Talks

1. Can Foundation LLMs Play Go (Weiqi/Baduk) via Text Protocols Alone? - Victor Zommers
2. Why Python is the best language for algorithmic trading - Richard Hickling @richardhickling
3. HangMAN vs AI - Kavit Tolia
4. Comedy Breeder - Samuel Joseph @tansakuu
5. Answering a dumb question with a smart bird feeder - Hugh Evans
6. AI Playgroup event - Ian Ozsvald
7. Mapping the Mind of a Large Language Model - Kefei Hu
8. What we've learnt from the world's largest AI red team - Sam Watts

Logistics Doors open at 6.30 pm (get there early as you'll need to sign in with building security). Talks start at 7:00 pm, with drinks afterwards from 9:00 pm at The Banker (EC4).

We have reduced capacity for this event, but there will be plenty of people to discuss data science questions with!

Please unRSVP in good time if you realise you can't make it. We're limited by building security on the number of attendees, so please free up your place for your fellow community members!

Venue: Carnival House, 100 Harbour Parade, Southampton, SO15 1ST 📢 Want to speak 📢: submit your talk proposal

Please note:

1. 🚨🚨🚨A valid photo ID is required by building security. You MUST use your initial/first name and surname on your meetup profile, otherwise, you will NOT make it on the guest list! 🚨🚨🚨
2. This event follows the NumFOCUS Code of Conduct, please familiarise yourself with it before the event.

If your RSVP status says "You're going" you will be able to get in. No further confirmation required. You will NOT need to show your RSVP confirmation when signing in. If you can no longer make it, please unRSVP as soon as you know so we can assign your place to someone on the waiting list.

*** Code of Conduct: This event follows the NumFOCUS Code of Conduct, please familiarise yourself with it before the event. Please get in touch with the organisers with any questions or concerns regarding the Code of Conduct. *** There will be pizza & drinks, generously provided by our host, Carnival UK. ***

Main Talks 1️⃣ The Python Powered Modern Data Stack - John Sandall The Modern Data Stack has brought a lot of new buzzwords into the data engineering lexicon: "data mesh", "data observability", "reverse ETL", "data lineage", "analytics engineering". The PyData Stack introduced pandas pipelines powering ETL workflows...clean code, tested code, data validation, perfect for in-memory workflows. As demand for self-serve analytics grows, new data sources bring more APIs to model, more code to maintain, DAG workflow orchestration tools, new nuances to capture ("the tax team defines revenue differently"), more dashboards, more not-quite-bugs ("but my number says this...").

Learn why the world shifted from ETL to ELT, what open-source Modern Data Stack tools you should know, with a focus on how dbt's Python integration is changing how data pipelines are built, run, tested & maintained. Beyond the latest trends & buzzwords, there is value to be gained by understanding Python's role in the future of data engineering.

2️⃣ Transformers Inside Out (Part 1.5) - Sam Joseph Large Language Models like GPT4 have catapulted transformers into the limelight, but how do they really work? How can you really code them? This talk presents an alternative representation of GPT internals and a new set of flow diagrams that more closely match the code in order to better understand transformers inside out!

Lightning Talks ⚡ ⚡1️⃣ Estimating cognitive workload using electroencephalography - Christoph Tremmel ⚡2️⃣ Benchmarking Time-Series Databases - Nick Thorne

Logistics Doors open at 6.30 pm, talks start at 7 pm. For those who wish to continue networking and chatting we will move to a nearby pub/bar for drinks from 9 pm.

Please unRSVP in good time if you realise you can't make it. We're limited by building security on the number of attendees, so please free up your place for your fellow community members!

Follow @pydatasoton (https://twitter.com/pydatasoton) for updates and early announcements. We are also on Instagram/Threads as @pydatasoton, and find us on LinkedIn.

Venue: 1 Angel Lane, EC4R 3AB

Please note:

1. 🚨🚨🚨A valid photo ID is required by building security. You MUST use your full real names on your meetup profile, otherwise, you will NOT make it on the guest list! 🚨🚨🚨
2. This event follows the NumFOCUS Code of Conduct, please familiarise yourself with it before the event.

If your RSVP status says "You're going" you will be able to get in. No further confirmation required. You will NOT need to show your RSVP confirmation when signing in.

If you can no longer make it, please unRSVP as soon as you know so we can assign your place to someone on the waiting list.

Code of Conduct: This event follows the NumFOCUS Code of Conduct, please familiarise yourself with it before the event. Please get in touch with the organisers with any questions or concerns regarding the Code of Conduct.

As always, there'll be free food & drinks, generously provided by our host, Man Group.

Main Talks 1️⃣ Simplifying Real-Time ML Pipelines with Quix Streams - Tomas Neubauer

As data volume and velocity continue to increase, the need for real-time machine learning (ML) is becoming more pressing. However, building real-time ML pipelines can be complex and time-consuming, requiring expertise in both ML and streaming application development. This talk will address this problem by introducing Quix Streams, an open-source Python library that makes it easy for data scientists and ML engineers to build real-time ML pipelines without having to learn the intricacies of building a streaming application from scratch.

2️⃣ Transformers Inside Out - Sam Joseph

Large Language Models like GPT4 have catapulted transformers into the limelight, but how do they really work? How can you really code them? This talk presents a new set of flow diagrams that more closely match the code in order to better understand transformers inside out!

Lightning Talks ⚡ ⚡1️⃣ Python in Excel - Mark Rotchell

A high level overview of the recent announcement of Python integration into Excel - what it looks like to have Python in a spreadsheet, why you might want to use it, and why I think it's a good thing for the Python community.

⚡2️⃣ Sometimes the music and playlists we hear don't hit our mood we are feeling, can AI help with this ? - Filip Makraduli

An AI song recommendation tool that tries to understand the vibe and feel of a song. A dataset of songs and their descriptions of moods and vibes is generated by promoting an LLM. Each song's vibe is encoded using a transformer model and saved as a vector index. Then this vector index is queried by similarity using the vector embedding of the user's input and the top N matches are returned.

Logistics Doors open at 6.30 pm (get there early as you have to sign-in via building security), talks start at 7 pm, drinks from 9 pm in the bar. We will have reduced capacity for this event but there will be plenty of people to discuss data science questions with!

Please unRSVP in good time if you realise you can't make it. We're limited by building security on the number of attendees, so please free up your place for your fellow community members!

Follow @pydatalondon (https://twitter.com/pydatalondon) for updates and early announcements.