Name: Future-proof energy systems with ML: tackling data drift & low-data forecasting
Start: 2024-11-28T17:00:00.000Z
End: 2024-11-28T21:00:00.000Z
Location: Dexter Energy Services B.V.

Join us for an insightful session as we explore the nuances of the job market for data professionals with a veteran recruiter. With years of experience in talent acquisition, our speaker will offer practical advice on navigating the competitive landscape of data careers. We'll delve into resume best practices, common pitfalls to avoid, and the qualities that make candidates stand out. Gain an insider’s perspective on the hiring process, learn how to make a lasting impression, and understand how to position yourself effectively, whether you're new to the field or pivoting into data. Don't miss this opportunity to hear real-world tips and strategies to enhance your job search success!
**THIS IS A FREE ONLINE EVENT, LINK TO BE ANNOUNCED**

Data Engineering Pilipinas - a PyData group

Myk Ogbinar

SandyGC

Josh Valdeleon

Navigating the Data Job Market:  Insights from a Veteran Recruiter

Online event

Welcome to the PyData Berlin November meetup!

We would like to welcome you all starting from 18:45. There will be food and drinks. The talks begin around 19.30 and the doors will close at 19:30. **Make sure to arrive on time!**

Please provide your first and last name for the registration because this is required for the venue's entry policy. If you cannot attend, please cancel your spot so others are able to join as the space is limited.

**Host**:
Bonial is excited to welcome you to this month's version of PyData.
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The Lineup for the evening

**Talk 1: Running Python data transformations at scale with dbt and Astronomer Cosmos**
**Abstract**: I will discuss how we built a tool using dbt and Astronomer Cosmos to orchestrate Python data transformations at scale. As part of a global team, we faced the challenge of developing and scaling data transformations for our entities across more than 50 countries. Our data scientists write these transformations to improve our machine learning models, and the need to manage such a large number of entities required an efficient and scalable solution. This tool streamlines the entire process, enabling data scientists to quickly develop data transformations, leverage built-in dbt tests for data validation, and seamlessly deploy these transformations to production environments. The integration of dbt and Astronomer Cosmos has significantly accelerated our workflows, ensuring robust and scalable data operations while also empowering our data scientists to deliver more value, faster.

**Speaker: Galuh Sahid** currently works as a Senior Machine Learning Engineer at Delivery Hero. She is also recognized as a Google Developer Expert in Machine Learning. She previously worked at Twitter and Gojek. She has developed and productionized various ML applications, including fraud detection, content moderation, and marketing using traditional ML, NLP, and computer vision. In her free time, Galuh enjoys painting and hiking.

**Talk 2:** **Anomaly Detection in Track Scenes**
**Abstract**: In the “Digitale Schiene Deutschland” initiative, Deutsche Bahn is developing an automated train driving system. To support this, we collaborated with them to create a machine learning solution that detects anomalous objects on and around tracks using onboard RGB cameras. Rather than recognizing specific object classes (e.g., people, signals), this system identifies any object and ranks it by anomaly. This presentation covers challenges, approaches, and the final solution: a unique pipeline using multiple machine learning components, including monocular depth estimation, segmentation, image embedding, and anomaly detection. The OSDAR23 dataset, containing 45 scenes with RGB, infrared, radar, and lidar data, aids in model finetuning and evaluation. Additionally, unannotated data was used for self-supervised learning.

**Speaker: Maximilian Trescher** studied physics in Berlin and Paris, PhD in theoretical physics in 2018 (Freie Universität Berlin). Then he worked 4 years (18-22) as a software engineer (Java, databases etc).
Since 2022 he is a machine learning Scientist at dida ([www.dida.do](http://www.dida.do)).

**Lightning talks**
There will be slots for 2-3 Lightning Talks (3-5 Minutes for each).
Kindly let us know if you would like to present something at the start of the meetup :)

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NumFOCUS **Code of Conduct**
THE SHORT VERSION
Be kind to others. Do not insult or put down others. Behave professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate for NumFOCUS.
All communication should be appropriate for a professional audience including people of many different backgrounds. Sexual language and imagery are not appropriate.
NumFOCUS is dedicated to providing a harassment-free community for everyone, regardless of gender, sexual orientation, gender identity, and expression, disability, physical appearance, body size, race, or religion. We do not tolerate harassment of community members in any form.
Thank you for helping make this a welcoming, friendly community for all.
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PyData Berlin

Valentina

Theodore Meynard

PyData Berlin 2024 November Meetup

Hussitenstraße 32

🗺 Hey PyData Hamburg Community 💚,
The PyData Hamburg community is hosting an exciting meetup on supply chain topics with a focus on AI. This event is sponsored by Blue Yonder and will take place at their new office located in the heart of the Altstadt. We are looking forward to an evening of learning and collaboration! (drum rolls & background music please♬ ♭)
The talk schedule is as follows:
1. **Artificial Intelligence in Logistics - Leveraging Digital Twins for AI-driven Price Optimization**: Intelligent pricing in logistics is tailored to customers and market conditions. We use artificial intelligence (AI) to generate optimized prices and a digital twin to simulate strategic decisions and KPIs. Our AI models face various challenges, including sparse data, configurable products, and local market conditions. Our ultimate goals are customer-specific price elasticities and AI predictions explainable to humans. In my presentation, I will explain how we use AI for price optimization and its integration into Kuehne+Nagel's daily operations.
2. **Let Them Talk! The Future of Supply Chain Management with Conversable Agents:** Discover how a new conversational, multi-modal, and agentic forecasting approach is set to transform demand planning by bringing the power of AI to all users. Learn how conversational agents are shaping the future of supply chain decision-making and making sophisticated forecasting tools accessible for everyone.
3. **The Fine Line of Bias Correction in Generative AI:** Bias correction in Generative Al can create both positive and negative impacts. While it can reduce harmful biases like discriminatory language, it can also limit open dialogue or influence information. This talk examines how biases emerge in Al, explores unintended consequences of bias correction, and addresses the technical and ethical challenges of mitigating biases without restricting discussion.
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🦸‍♀️🦸🏾🦸🏼‍♂️🦸🏿‍♂️Who Will Be There:
\- Lifelong tech enthusiasts
\- Scientists
\- Open source enthusiasts
\- Experts in the world’s most pressing challenges \(e\.g\.\, AI\, forecasting\, logistics\, supply chain\, and more\!\)
\*\*\*
⭐️Agenda⭐️:
\- 18:00 \- Open Doors
\- 18:20 \- Short Intro
\- 18:30 \-19:00 First Talk and Questions
\- Break \-
\- 19:10 \- 19:40 Second Talk and Questions
\- 19:45 \- 20:15 Third Talk and Questions
\- 20:15 \- 21:00 Networking & Pizza 🍕

\*\*\*
📣Speakers💫
[Talk 1: ⭐ Dr. Dirk-Sören Lühmann](https://www.linkedin.com/in/dirk-luehmann/)
Dr. Dirk-Sören Lühmann leads Kühne + Nagel’s Data Science team
[Talk 2: ⭐️ Morteza Khani](https://www.linkedin.com/in/mortezakhani)
AI & Forecasting Expert, Founder
[Talk 3: ⭐️ Dr. Annemarie Paul](https://www.linkedin.com/in/dr-annemarie-paul/)
Data Science team Lead & AI Strategist
\*\*\*
Special Perks:
🎫€Free
🍕Food & Snacks on us!
🍻Drinks on us!
\*\*\*
Where:
📍[Blue Yonder](https://maps.app.goo.gl/AaoU92pYAJuVGNeS9)
c/o Mindspace, Rödingsmarkt 9, 20457 Hamburg (1st Floor)
\*\*\*
❗️“Space is limited, and so is the maximal occupancy of the Mindspace venue – so please register to attend! If you happen to not come after all, please cancel your registration so others can take your spot.”
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💚 WHO ARE WE - PyData Hamburg:
Your Hamburg local AI & Data Community-
PyData is a community for developers and users of open-source data tools. PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. The PyData Code of Conduct governs this meetup.

PyData Hamburg

Kai-Ti Wu

Marcel Hebing

Christopher Holmes

PyData Hamburg November 21 Meetup

**Venue**: Carnival House, 100 Harbour Parade, Southampton, SO15 1ST
**📢 Want to speak 📢: [submit your talk proposal](https://bit.ly/pydataSoton-talks)**

**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](https://numfocus.org/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](https://numfocus.org/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.
\*\*\*

**Mastering Data Flow: Prefect Pipelines** **Workshop - [Adam Hill](https://www.linkedin.com/in/adambenhill/) & [Chris Frohmaier](https://www.linkedin.com/in/cfrohmaier/)**
Join us for an engaging workshop where we'll dive deep into the world of data engineering with Prefect 3. Throughout the session, participants will explore the following key topics:

* Overview of Prefect and its core features
* Understanding the Prefect ecosystem and its integration with popular data science tools
* Setting up a Prefect environment: Installation, configuration, and project setup

**Building Data Pipelines:**

* Data ingestion: Fetching data from various sources including RSS feeds, APIs, and databases
* Data transformation and manipulation using Prefect tasks and flows
* Data storage and persistence: Storing processed data into local databases such as MongoDB or SQL
* Integrating machine learning models for advanced data processing and analysis within Prefect workflows

**Advanced Techniques and Best Practices**:

* Implementing error handling and retry strategies for fault tolerance and reliability
* Exploring Prefect's advanced features such as parallel execution, versioning, and dependency management

By the end of the workshop, attendees will have gained a comprehensive understanding of Prefect 3 and its capabilities, empowering them to design, execute, and optimise data pipelines efficiently in real-world scenarios.

We invite you to join us on this exciting journey of mastering data flows with Prefect!

**Instructions to prepare in advance**
**Workshop Materials and Requirements:**
In advance of the workshop please visit the github repo here: [https://github.com/Cadarn/PyData-Prefect-Workshop](https://github.com/Cadarn/PyData-Prefect-Workshop). Clone a copy of the repository and follow the setup instructions in the README file including:

* Setting up a new Python environment with all the required modules
* Installing Docker and Docker Compose if necessary and then running the docker compose file so that local copies of the software images are downloaded in advance.
* Create a free MongoDB Atlas account and setup a project/database for the workshop

Please follow the instructions in advance of attending the workshop/

**Please note this is a practical session and you will need to bring your own laptop. We recommend you bring it fully charged, if you can, as there may not be enough plug sockets for everyone to use at the same time.**

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

PyData Southampton

Claire Loptson

Adam Hill

Robin Wilson

PyData Southampton - 11th Meetup

Carnival House

**DETAILS**

It's almost exactly one year ago; time for another co-organized meetup with **Dexter Energy** on **November 28 at 18:00 CET** at their office in Amsterdam - [Joan Muyskenweg 22, 1096 CJ Amsterdam](https://www.google.nl/url?sa=t&source=web&rct=j&opi=89978449&url=/maps/place//data%3D!4m2!3m1!1s0x47c7ad3bbce2b2a5:0xce460eef247424e0%3Fsa%3DX%26ved%3D1t:8290%26ictx%3D111&ved=2ahUKEwicg56l-NSJAxW6gf0HHeBhAM8Q4kB6BAhBEAM&usg=AOvVaw2rCl_8hg5L8DXcmJSY3axn). On this meetup you'll learn more about how to use Bayesian modeling for sparse data coverage, and additionally different methodologies and challenges of detecting data drift will be discussed.

Get energized by practical data science use cases in the space of forecasting and data drift, knowledge sharing and of course networking; see you all soon!

**SCHEDULE**

18:00 - 19:00: Walk-in with drinks and bites & welcome!
19:00 - 19:45: **Using Bayesian modeling to Overcome Low Data Coverage** by [Aletta Heemskerk](https://www.linkedin.com/in/aletta-heemskerk-1a3263134/)
19:45 - 20:00: Break
20:00 - 20:45: **Adapting to change: dealing with data drift in energy waste prevention** by [Tatjana Puskarov](https://www.linkedin.com/in/tatjana-puskarov/)
20:45 - 22:00: Networking and drinks

**TALKS**

**\[Talk 1\]: Using Bayesian modeling to Overcome Low Data Coverage** by Aletta Heemskerk

A key part of forecasting wind power generation is fitting the wind speed-energy curve. There are various ways of estimating this relation. Common options are a parametric model, basically a good baseline, or using Machine Learning.

However, some of these methods can be prone to outliers or struggle when limited samples are available. Alternatively, one can use Bayesian modeling. This approach yields easy-to-interpret results and allows one to handle sparse data coverage.

In this talk, we will start with the foundation of Bayesian statistics and introduce the problem at hand. We will cover how to apply HMC NUTS using NumPyro including the specification, fitting, and validation using the business case of forecasting wind energy in low data regimes.

**\[Talk 2\]: Adapting to change: dealing with data drift in energy waste prevention** by Tatjana Puskarov

At Sensorfact we aim to reduce the human environmental footprint by eliminating all waste in industry, a large part of which comes from idling machines. We have set up a machine learning system to do this based on real time power consumption data. The machine-level models underlying this system are trained on a reference period and continuously predict in near real time. However, as machines wear out or get serviced, or as our customers make changes in their production, the data drifts - leading to a diminishing performance of our ML system and potentially unnoticed preventable standby consumption. We have therefore implemented data drift detection in the system lifecycle - with data drift alerts, we can retrain our models in time to ensure their quality. In this talk, we will discuss the methodologies and challenges of detecting drift and the solution that was selected for our use case.

**NOTE:**
Our team will be ready to assist with check-in starting at 18:00, so please arrive a bit early if possible.

Since we can only host a limited amount of attendees for this meetup event, if you cannot join the event, update your status to "**not going**" so you can give your spot to the folks on the waitlist. Thanks for your help!

**DIRECTIONS**

**Address:**
Dexter Energy Amsterdam Office
[Joan Muyskenweg 22, 1096 CJ Amsterdam](https://www.google.nl/url?sa=t&source=web&rct=j&opi=89978449&url=/maps/place//data%3D!4m2!3m1!1s0x47c7ad3bbce2b2a5:0xce460eef247424e0%3Fsa%3DX%26ved%3D1t:8290%26ictx%3D111&ved=2ahUKEwicg56l-NSJAxW6gf0HHeBhAM8Q4kB6BAhBEAM&usg=AOvVaw2rCl_8hg5L8DXcmJSY3axn)

**By Bike:**
If you’re already in Amsterdam or nearby, biking is a convenient option. Use Google Maps or a similar app for a bike-friendly route. Most paths will guide you to Amstelkwartier west.

**By Public transport:**
Take a metro to Amsterdam Overamstel Station. The Dexter Energy office is located next to the Overamstel metro station; it's just a 250m walk.

PyData Amsterdam

Alexander Oude Elferink

Louis de Bruijn

fatih demir

Future-proof energy systems with ML: tackling data drift & low-data forecasting

Dexter Energy Services B.V.

PyData

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