Conferences / PyData
PyData London 2024
Jun 14–16, 2024 · Leonardo Royal Hotel London Tower Bridge, London, United Kingdom
- Conference
- PyData Data science & ML
- Dates
- Jun 14, 2024 – Jun 16, 2024
- Venue
- Leonardo Royal Hotel London Tower Bridge
- Place
- London, United Kingdom
- Format
- In person
- Status
- Past
- Attendance
- —
- Website
- pydata.org
- Recorded
- 11 sponsors · 67 speaker appearances
- Notes
- Tutorials Friday 14 June, talks 15-16 June; tickets sold out. Sponsor names identified from logo links/filenames; Anaconda and NVIDIA also listed as conference social sponsors. Speakers: all sessions in the pretalx schedule export (self-hosted pretalx, retrieved via the Wayback Machine); affiliations parsed from pretalx bios, null where not stated. Talk URLs point to the now-defunct pretalx host. Ticket prices not found.
Ticket prices
No ticket prices recorded
Sponsors 11
Speakers and talks 67
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Dr. Matthew Crooks | BBC | Keynote | Keynote- Data: Faithful or Traitor? | — |
| Dr. Rebecca Bilbro | — | Keynote | Keynote- Dr. Rebecca Bilbro- Mistakes were made | Data science ten years in | — |
| Tania Allard | Quansight | Keynote | Keynote-Tania Allard-The art of building and sustaining successful OSS tools and infrastructure | — |
| Aaron Byrne | Barclays | Talk | Training and Deployment of ML models at scale in a Risk Controlled Banking Environment | — |
| Adam Glustein | Point72 / Cubist Systematic Strategies | Talk | Enabling real-time insights through stream processing in Python | — |
| Adam Hill | — | Tutorial | Mastering Data Flow: Empower Your Projects with Prefect's Pipeline Magic | — |
| Alex Owens | — | Talk | What a serverless database means for users | — |
| Alexander Darby | Palo Alto Networks | Talk | 5 Things I Learnt from Causing a Cloud Provider Outage | — |
| Alkiviadis Kariotis | impruvo | Talk | Navigating through financial data challenges by harnessing the power of synthetic data | — |
| Andrea Melloncelli | Apply Quantum | Talk | Quantum artificial intelligence | — |
| Andy Fundinger | Bloomberg | Talk | Adventures in not writing tests | — |
| Andy Terrel | University of Texas and Texas Advanced Computing Center | Tutorial | GPU Development in Python 101 | — |
| Anna-Lena Popkes | — | Talk | When and how to start coding with kids | — |
| Antonio Feregrino | Simply Business | Talk | Generating embeddings for Yu-Gi-Oh Cards: A NumPy Approach to Represent Complex Data | — |
| Arkadiusz Trawiński, PhD | — | Talk | Log messages processing using NLP tools | — |
| Arun Kundgol | — | Talk | Training and Deployment of ML models at scale in a Risk Controlled Banking Environment | — |
| Carlos Samey | IDinsight | Talk | Strategic Planning in Public Health: Linear Programming for Resource Allocation | — |
| Cas Wognum | Valence Labs | Talk | Using Zarr as a universal and efficient format for drug discovery datasets in Polaris | — |
| Cheuk Ting Ho | CMD Limes | Tutorial | [Unconference] How to define open source AI | — |
| Chi Wang | — | Talk | Building Multi-Agent Generative-AI Applications with AutoGen | — |
| Chris Fonnesbeck | Philadelphia Phillies | Tutorial | Probabilistic Programming and Bayesian Computing with PyMC | — |
| Chris Wilkin | Tesco | Talk | Content Orchestration: Growing user engagement with RL-driven personalisation | — |
| Dan Gibson | Personify AI | Tutorial | An Introduction to Retrieval Augmented Generation | — |
| Deb Nicholson | Python Software Foundation | Talk | Open Source Leadership: What to Give Away and What to Bring In | — |
| Deepyaman Datta | Voltron Data | Tutorial | Analytics engineering without dbt? Building the composable Python data stack with Kedro and Ibis | — |
| Diego Colombo | Microsoft | Talk | Building Multi-Agent Generative-AI Applications with AutoGen | — |
| Elena Chatzimichali, PhD | Deree | Talk | Navigating through financial data challenges by harnessing the power of synthetic data | — |
| Emeli Dral | Evidently AI | Talk | The evolving conversation: How continuous testing keeps your LLM on track. | — |
| Emlyn Clay | — | Talk | Protein folding and what it means for drug discovery | — |
| Evangelos Tsilikas | Public Power Corporation | Talk | Navigating through financial data challenges by harnessing the power of synthetic data | — |
| Hajime Takeda | — | Talk | Uplift Modeling: How to Enhance Customer Targeting in Marketing with Causal Machine Learning | — |
| Harriet Yue Huang | — | Talk | Achieving Concurrency in Streamlit with a RQ scheduler, Building Responsive Data Applications | — |
| Hendrik Makait | Coiled | Talk | Observability for Dask in Production | — |
| Ian Ozsvald | — | Talk | Leaders at PyData | — |
| Ines Montani | Explosion | Talk | Taking LLMs out of the black box: A practical guide to human-in-the-loop distillation | — |
| Isaac | — | Tutorial | Multimodal Deep Learning in the Real World | — |
| Jacob Tomlinson | NVIDIA | Tutorial | GPU Development in Python 101 | — |
| James Powell | — | Talk | Are generator-coroutines really the answer? | — |
| Jeroen Overschie | Xebia | Talk | Are you ready for MLOps? 🫵 | — |
| Jetze Schuurmans | — | Talk | Are you ready for MLOps? 🫵 | — |
| Jim Dowling | KTH Royal Institute of Technology | Talk | Function Calling for LLMs | — |
| John Carney | — | Talk | PyData Organizers Meetup | — |
| John Sandall | Coefficient | Talk | Fine Tuning: Building A Folk Music Recommendation System with LLMs | — |
| Juan Luis Cano Rodríguez | QuantumBlack | Tutorial | Analytics engineering without dbt? Building the composable Python data stack with Kedro and Ibis | — |
| Kehinde Richard Ogunyale | — | Tutorial | Graph databases and Retrieval Augmented Generation | — |
| Kishan Manani | — | Talk | Backtesting and error metrics for modern time series forecasting | — |
| Konstantinos Kogias | Deree College | Talk | Navigating through financial data challenges by harnessing the power of synthetic data | — |
| lex Avstreikh | — | Tutorial | Let AI help you find the Best Bar. Build a Real-Time Personalized AI Recommender System powered by a LLM. | — |
| Luca Baggi | — | Talk | Uncertainty estimation at scale with functime, Polars and conformal predictions | — |
| Marco Gorelli | Quansight | Tutorial | How you (yes, you!) can write a Polars Plugin | — |
| Nick Gates | — | Talk | 10 years of Parquet: what’s next? | — |
| Nick Radcliffe | Quadstone | Tutorial | Test-Driven Data Analysis in Python | — |
| Noé Achache | Sicara | Talk | RAG for a medical company: the technical and product challenges | — |
| Patrick Hoefler | Coiled | Talk | Dask DataFrame 2.0 - Comparison to Spark, DuckDB and Polars | — |
| Quazi Nafiul Islam | Sonar | Talk | From Eggs to Poetry: The Evolutionary Saga of Python Packaging | — |
| Raymond Cunningham | — | Tutorial | Let AI help you find the Best Bar. Build a Real-Time Personalized AI Recommender System powered by a LLM. | — |
| Rhythm Patel | Bloomberg | Talk | No More Raw SQL: SQLAlchemy & ORMs | — |
| Sefik Serengil | — | Talk | Behind the Pixels: The Art and Science of Deep Face Recognition in Python | — |
| Sofie Van Landeghem | — | Talk | How to uncover and avoid structural biases in evaluating your Machine Learning/NLP projects | — |
| Stamatios Lykos | Asappien | Talk | Navigating through financial data challenges by harnessing the power of synthetic data | — |
| Sultan Al Awar | Amazon Web Services | Tutorial | From Classic to Cutting Edge Text Classification: Generating Customers Insights with Topic Modelling and HuggingFace SetFit Method | — |
| Thomas Wiecki | PyMC Labs | Tutorial | Probabilistic Programming and Bayesian Computing with PyMC | — |
| Tomara Youngblood | — | Talk | Lightning Talks- Salisbury | — |
| Tomara Youngblood | — | Talk | Lightning Talks- Warwick Room | — |
| Tun Shwe | Quix | Talk | Moving from Offline to Online Machine Learning with River | — |
| Victor Dibia | Microsoft | Talk | Building Multi-Agent Generative-AI Applications with AutoGen | — |
| Wojciech Matejuk | — | Talk | Can machines play the piano? Deep learning approach to modelling emotional nuance of musical performance. | — |