Chaos Computer Club - archive feed

Der Publisher ist Open Source Software zum Veröffentlichen von Podcasts. Wir schauen auf den aktuellen Stand und blicken auf die letzten Jahre Entwicklung zurück. Licensed to the public under https://creativecommons.org/licenses/by/4.0/ about this event: https://pretalx.c3voc.de/subscribe11/talk/EUQJVQ/

Eine Zeitreise in die letzten 50 Jahre der Entwicklung individueller Kommunikation in Netzen und warum Podcasts zu einer der wichtigsten Medienformen geworden sind. Die Entwicklung individueller Kommunikation im Internet und seinen Vorläufern musste viele Umwege gehen um dort zu landen, wo sie heute steht. Der Vortrag blickt zurück auf die wichtigsten technischen und sozialen Entwicklungen im Internet, die die Basis für Podcasts gelegt haben, wie wir sie heute kennen. Licensed to the public under https://creativecommons.org/licenses/by/4.0/ about this event: https://pretalx.c3voc.de/subscribe11/talk/W8P7CU/

Podcasts sind en vogue - doch wie startet man einen, wenn man absoluter Neuling ist? Neben einem spannenden Thema braucht es vor allem passende Tools für die Produktion und Veröffentlichung sowie eine solide inhaltliche Planung samt Branding. In diesem Talk teile ich meine Lessons Learned nach einem Jahr "ThinkPad-Museum". Podcasts erfreuen sich großer Beliebtheit - das Angebot ist größer als in absehbarer Zeit konsumiert werden könnte. Schön, wenn man selbst mit einem spannenden Thema zur Vielfalt beitragen möchte. Doch, wie kommt man als Neuling zum gewünschten Ergebnis? Mit spannenden Inhalten ist ein Grundstein gelegt, der mithilfe von passendem Audio-Equipment und -Tools weiter reifen kann. Ein Branding mit Wiedererkennungswert kann den weiteren Erfolg maßgeblich beeinflussen. Eine solide inhaltliche und zeitliche Planung ist notwendig - nicht zuletzt, wenn Gäst:innen das Format interaktiver machen sollen. Ist die Folge dann im Kasten, stellt sich die Frage nach dem Hosten des Feeds sowie der Bewerbung der jeweiligen Episoden. Zu guter Letzt kann Analytics dabei unterstützen, mehr über die Zuhörerschaft zu erfahren. In diesem Talk gebe ich euch einen Einblick in meine Arbeit beim ThinkPad-Museum Podcast und zeige euch meine Lessons Learned. Licensed to the public under https://creativecommons.org/licenses/by/4.0/ about this event: https://pretalx.c3voc.de/subscribe11/talk/TFCEPP/

Thank you for joining us today. See you next time! about this event: https://c3voc.de

We are happy to announce Lightning Talks to this year's conference again! They are open to everyone 😊 about this event: https://c3voc.de

Ich hatte eine lustige Podcast-Idee. In diesem Talk dreht es sich um die 10 Dinge, die ich nach einem Jahr und hundert Folgen gelernt habe. Ein Talk für alle, die auch eine Podcast-Idee haben und nicht wissen, was auf sie zu kommt, aber danach sofort loslegen möchten. Wie fängt man an? Was tun, wenn Gäste kein eigenes Mikrofon haben aber auch keinen Computer? Was, wenn man im Hotel zum Interview verabredet ist, aber niemand davon weiß? Sind drei Backups zu viel? Wie bleibt man Freunde, wenn man 60 Stunden miteinander redet? Wie erklärt man der größten Medienagentur Deutschlands, dass das alles doch nur eine Schnapsidee ist? Wie fühlt es sich an, plötzlich beim größten Comedy-Festival dabei zu sein, weil die nicht wissen, dass man nur 500 Hörer*innen hat? Mit zwei Freund*innen hatte die Idee, die Komödie "Kein Pardon" von 1993 Minute für Minute zu besprechen. Was nach einer witzigen Idee klingt, wurde zu einem harten Ritt. Der Talk soll motivieren, es uns trotzdem gleich zu tun. Ein Talk über 10 Fehler, 10 Missverständnisse und 10 Überraschungen. Licensed to the public under https://creativecommons.org/licenses/by/4.0/ about this event: https://pretalx.c3voc.de/subscribe11/talk/8JFHS3/

Retrieval Augmented Generation (RAG) has been used to mitigate hallucination issues from LLMs and rapidly provide LLMs with external knowledge that were not part of the pre-training data. While tutorials offer convenient ways to build POCs quickly, transitioning these prototypes to production environments often catches us off-guard with unforeseen challenges. This talk takes a deeper dive into the topics that are often missing from cookbooks and tutorials yet are crucial in scaling your RAG prototype to production. Our discussion will use real examples to help you better understand some of the best practices in production RAG for observability, security, scalability, and fault tolerance. about this event: https://c3voc.de

Ich habe beschlossen, aus meinen Projekten eine Podcast-Kooperative zu machen. Warum und wie erkläre ich hier. In diesen Vortrag möchte ich meine Beweggründe für das Gründen einer Kooperative erklären. Warum dieser Ansatz für freie Podcastende eine gute Möglichkeit ist, und warum wir ihn brauchen. Licensed to the public under https://creativecommons.org/licenses/by/4.0/ about this event: https://pretalx.c3voc.de/subscribe11/talk/C97GAF/

In the pursuit of classifying train stations from Open Railway Maps data, for Europe's largest rail cargo company. Initially, the project focused on developing a robust deep learning framework, which required extensive manual labeling of images to train the model effectively. Recognizing the impracticality and time-consuming nature of manual labeling, we conceptualized an approach to expedite the labeling process using cluster algorithms and graph information. Our method involved an automated labeling algorithm, which significantly accelerated the annotation phase. This algorithm demonstrated remarkable efficiency, automatically labeling images with high accuracy, thereby drastically reducing the manual effort involved. During the implementation, we discovered that our automated labeling algorithm was, in itself, the comprehensive solution for the classification task we aimed to address. This realization highlighted that our initial objective of deploying a deep learning model could be achieved through "classic" means. In conclusion, our project unveiled that the automated labeling algorithm was not just a tool to facilitate deep learning, but an effective standalone solution in itself. This unexpected outcome emphasizing that sometimes, the journey towards deep learning can reveal simpler, yet equally powerful, solutions. Damn, as all data scientists deep down, we wanted to take advantage of some sexy deep learning and ended up with a great, but not so sexy core data science solution. about this event: https://c3voc.de

Begrüßungsveranstaltung und Standortbestimmung der unabhängigen deutschen Podcastszene Mehr als fünf Jahre sind vergangen seit der letzten SUBSCRIBE und es wird eine Herausforderung, die alte Dynamik wieder aufzunehmen, doch sind viele Projekte wie Podlove und Ultraschall immer noch wichtig und aktiv und auch die Intensität des Podcastings hat nicht abgenommen. Podcasts sind mittlerweile komplett im Mainstream angekommen und viele Hobby-Podcaster haben dieses Hobby zum Beruf machen können. Zelebritäten und und andere Wichtigtuer haben alle Podcasts als wichtiges Outlet erkannt und die unterschiedlichsten Finanzierungsmodell werden ausprobiert. Was bleibt von der freien Szene und welche Bedeutung wird sie künftig haben? Wir versuchen eine Standortbestimmung und Selbstreflexion. Licensed to the public under https://creativecommons.org/licenses/by/4.0/ about this event: https://pretalx.c3voc.de/subscribe11/talk/YVHJZC/

Join us on two Vision-Language Adventures! We'll uncover the information hidden inside big image collections with Vision-Language Models (VLMs) showing us the way. Who knows which forgotten gems await us? In the first part, we'll use CLIP and FAISS to go on a treasure hunt in your photo collection. You'll learn how to filter through millions of images in a breeze, using natural language. Bye-bye endless scrolling, hour-long tagging, and frustrated folder searching. In the second part, we will harness the power of VLMs to help us caption images – translating pixels to words. Then we'll make use of the BERTopic library to reveal even deeper insights into your photo collections. By the end of this talk, you'll be equipped with the knowledge and tools to unlock new insights, identify patterns, and make your image data work harder for you. This talk is for an intermediate audience – it is good if you bring some knowledge in Computer Vision, NLP or just general Deep Learning. about this event: https://c3voc.de

Apache Spark is a powerful framework often used alongside Python for big data processing. You've seen its capabilities, but what powers its impressive performance? In this session, we'll delve into the internal workings of Spark. We'll explore concepts like Resilient Distributed Datasets (RDDs), which are fundamental to Spark's fault tolerance. We'll see how Spark distributes tasks across a cluster, leveraging Python's strengths in parallel processing. Finally, we'll uncover the secrets of in-memory computations, the key to Spark's blazing speed. Gaining a deeper understanding of Spark's internals, especially within the Python ecosystem, empowers you to: Optimize your Python big data applications for peak performance. Troubleshoot issues more efficiently. Write effective Spark code that unlocks its true potential and complements your Python expertise. Whether you're a data scientist, developer, or simply curious about big data, this talk will bridge the gap between Python and Spark. about this event: https://c3voc.de

XGBoost is considered a state-of-the-art model for regression, classification, and learning-to-rank problems on tabular data. Unfortunately, tree-based ensemble models are notoriously difficult to explain, limiting their application in critical fields. Techniques like SHapley Additive exPlanations (SHAP) and Explainable Boosting Machine (EBM) have become common methods for assessing how much each feature contributes to the model prediction. This talk will introduce SHAP and EBM, explaining the theory behind their mechanisms in an accessible way and discussing the pros and cons of both techniques. We will also comment on Python snippets where SHAP and EBM are used to explain a gradient boosting model. Attendees will walk away with an understanding of how SHAP and EBM work, the limitations and merits of both techniques, and a tutorial on how to use these methods in Python, courtesy of the "shap" and "interpret-ml" packages. about this event: https://c3voc.de

Recently, quantum machine learning algorithms have become popular due to a drastic increase in the power of quantum computation. Analysis of images with 10^54 pixels, easy encoding of Fourier series-like data, generation of novel chemical molecules – and all that with a couple of Python code lines! It's only left to choose a framework for trying out next-level deep learning models … but which one? The "grandfather" of Python quantum computing packages, PennyLane, with tons of user-friendly tutorials – or maybe a Qiskit, which runs naturally on IBM quantum computers, and moreover in February 2024 got a first major release? The answer is not that obvious, and together, we'll look at the pros and cons of both via training quantum circuits, assessing compatibility with popular Python machine learning packages – and all that on examples of real-world problems from financial and natural sciences. about this event: https://c3voc.de

While we have witnessed spectacular advancements in Machine Learning over the past months and years, robustness of results and establishment of causal relations remain lacking. During this talk we will walk you through an example of using causal Machine Learning techniques to estimate causal, heterogeneous treatment effects with Open Source Python tooling. Learning causal relationships – in contrast to mere correlations – is of great importance for many applications where we'd like to learn how to intervene with the real world: To whom should we administer which medical drug? To whom should we offer a marketing voucher? For which automated processed should we make a human expert intervene? In such situations we'd like to rest assured our decision don't just rely correlations – potentially tainted by common confounders. Rather, we'd like to make causal statements about the heterogeneous effects of administering a treatment. In terms of making this happen, the field of Causal Inference has been able to incorporate progress from Machine Learning in theory. Yet, in practice, applications remain challenging: tooling is still somewhat immature and little examples to follow exist. Therefore, we would like to walk you through a case study of estimating causal, heterogeneous treatment effects with Open Source Python tooling. about this event: https://c3voc.de

In the rapidly evolving field of Artificial Intelligence (AI), the importance of understanding model decisions is becoming increasingly vital. This talk explores why explanations are crucial for both technical and ethical reasons. We begin by examining the necessity of explainability in AI systems, particularly in mitigating unexpected model behavior, biases and addressing ethical concerns. The discussion then transitions into Explainable AI (XAI), highlighting the differences between interpretability and explainability, and showcasing methods for enhancing model transparency. A real-world examples will demonstrate how these concepts can be practically employed to improve model performance. The talk concludes with reflections on the challenges and future directions in XAI. about this event: https://c3voc.de

Welcome to the Python Summit! about this event: https://c3voc.de

Die Hoffnung ist gross, dass Digitalisierung und künstliche Intelligenz unser Gesundheitswesen revolutionieren wird und Menschen schneller und besser heilen kann als bisher. Doch ist diese Hoffnung gerechtfertigt oder nur ein schöner Traum? André Baumgart arbeitet beim Verband Zürcher Krankenhäuser und ist für die Themen Qualität, Patientensicherheit und Digitalisierung verantwortlich. Er wird uns einen profunden Überblick über die aktuelle Lage geben: Welche Tools nutzen die Leistungserbringern, welche stehen uns Patientinnen und Patienten zur Verfügung; Was kann künstliche Intelligenz heute schon leisten und was in naher Zukunft; Aber auch kritische Themen wie gläserner Mensch und Datenschutz werden angesprochen. about this event: https://www.digitale-gesellschaft.ch/event/netzpolitischer-abend-zu-stand-der-entwicklung-der-staatlichen-e-id/

Thank you for joining us today. See you next time! about this event: https://c3voc.de

We are happy to announce Lightning Talks to this year's conference again! They are open to everyone 😊 about this event: https://c3voc.de

In a brief review of the history of Python at Hamilton, we learn the different uses of Python and the great libraries that are available to simplify the life of an engineer. From device drivers and abstraction of complex processes to data acquisition, analysis and visualization, Python provides a one-stop shop to help developers get to their goals quickly. With an outlook, we show how laboratory specialists and researchers will be able to build on a solid ground in the future. about this event: https://c3voc.de

The website of the Hypothesis project boldly asserts: "Normal 'automated' software testing is surprisingly manual. Every scenario the computer runs, someone had to write by hand. Hypothesis can fix this." While it's debatable whether property-based testing should fully replace the manual parametrization of tests with different inputs and outputs, there's no doubt that Hypothesis is a powerful tool for uncovering bugs nobody would even have considered looking for. In fact, during its development, the authors of Hypothesis accidentally discovered countless bugs in CPython and libraries, thus coining the term "The Curse of Hypothesis". The framework, although incredibly powerful, might seem overwhelming at first. In this talk, I will demonstrate how even simply throwing random strings at functions can reveal surprising bugs. From there, we'll progress towards generating more complex data, which will be less daunting than it initially appears. You'll also see how Hypothesis seamlessly integrates with various ecosystems and can be a valuable tool in any developer's toolkit. about this event: https://c3voc.de

Python has never been good at parallel computing. Multi-threading doesn't scale beyond a handful of threads because of the notorious GIL (Global Interpreter Lock). Multi-processing feels like a cumbersome workaround that increases complexity and overhead. And yet, we're firmly in an era of multicore machines, big data, and massive ML models that require all the compute they can get. Python, otherwise the star of data science and ML, doesn't really shine when it comes to parallel workloads. But that is finally changing! There is more focus and progress happening in this area than ever before, and promising leaps forward are on the horizon. Subinterpreters, already merged in 3.12, offer a tentative step towards making the GIL less than "global" … while the free-threading build of Python 3.13 offers a path towards removing the GIL entirely in the future. Let's explore these new developments and look at how they work, what they do and do not solve, and how we can take advantage of them. about this event: https://c3voc.de

It is common knowledge that floating point numbers (`float`) are tricky. When misused, floats may lead to construction disaster – I will mention some notable accidents. But mainly, I will dig the topic from Python interface and rounding methods (`int` vs `round`, `divmod`, `math` library), via special symbols (`NaN`, `Inf`, `-0.0`, …), invoking different processor modes (`FLT_ROUNDS`), down to the bits of IEEE 754 standard. about this event: https://c3voc.de

asyncio is the de-facto standard for asynchronous programming in Python and enables concurrent operations without using threads or processes. In this talk, we will delve into the technical details of asyncio and show how it can be used to improve the performance of Python applications. We will start by discussing the difference between threading, multiprocessing and async programming. Then, we will introduce the basic building blocks of asyncio: Event loops and Coroutines. We will dive deep into the way Coroutines work, discussing their origins and how they are linked to Generators. Next, we will look at Tasks, which are a higher-level abstraction built on top of Coroutines. Tasks make it easy to schedule and manage the execution of Coroutines. We will cover how to create and manage Tasks and how they can be used to write concurrent code. Finally, we will also cover some more advanced topics such as Async Loops and Context Managers, and how to handle errors and cancellations in asyncio. Whether you are new to asyncio or have experience with it, this talk will provide valuable insights and tips for leveraging its full potential. By the end of this talk, you will have a better understanding of how asyncio works, and how to use it to create efficient, high-performing Python applications. about this event: https://c3voc.de

"Code Makeover: Mastering the Art of Python Refactoring" is your guide to transforming cluttered Python scripts into models of efficiency and readability. Discover the art of refining your code without losing your mind in the process. From recognizing the need for a makeover to applying the finishing touches, this talk will equip you with the strategies, best practices, and cautionary tales to ensure your code not only works beautifully but is also a joy to read and maintain. about this event: https://c3voc.de

Network automation is important for efficient and reliable network management. In simple terms it means using software to automate tasks like configuring or testing network devices like routers or switches. This increases the speed of deploying new configurations while reducing human error – a win-win situation for everyone! This talk introduces Netmiko, a powerful yet simple Python library for network automation. Netmiko provides an easy-to-use interface for SSH-based interactions with network devices. The syntax of Netmiko is easy to understand and it's vendor agnostic approach let's you automate all kinds of network devices. I'll show you how Netmiko works, starting with building your inventory of devices and connecting to them. Then we'll move on to sending config commands and configuring the devices. Finally, we'll verify if the config was applied successfully. By the end of this talk, you will be able to use Netmiko to automate your own network devices! about this event: https://c3voc.de