![Foto de portada de ODSC Data Science Madrid](https://secure.meetupstatic.com/photos/event/f/0/c/clean_505803852.webp)
De qué se trata
ODSC brings together the open source and data science communities with the goal of helping its members learn, connect and grow.
The focus of this Meetup group is to allow ODSC to work with Meetup groups, non-profits, and other organizations to present informative lectures, workshops, code sprints and networking events to help grow the use of open source languages and tools within the data science and data-centric community. As such, our specific goals are:
1. Build a collaborative group to work with other Meetup groups, non-profits, and other organizations.
2. Promote the use of open source languages and tools amongst data scientists and others.
3. Host educational workshops.
4. Spread awareness of new open source languages and tools that can be used in data science.
5. Contribute back to the open source community.
Who is this meetup for?
• Data engineers, analysts, scientists, and other practitioners
• R, Python and other software engineers who work with data or want to learn
• Data visualization developers and designers
• Non-technical team leads, executives, and other decision makers from data centric startups and large companies looking to utilize open source tools
Get Involved with our Meetups:
• Meetup/Webinar Speaker Submission Form https://forms.gle/STEDWxgWBMnLnt8F8
• Suggest a Meetup Topic Form
https://forms.gle/FAnBGMnC6puP1zLs6
• Volunteer Form
https://forms.gle/rJB2k8ZvU7mj1R3c8
• Host or Sponsor Form
https://forms.gle/bVdnzttfSuKkWrHq5
• Showcase your Startup Form
https://forms.gle/2Z31dmGPe7RTw28B9
ODSC Links:
• Get free access to more talks/trainings like this at Ai+ Training platform:
https://hubs.li/H0Zycsf0
• Facebook: https://www.facebook.com/OPENDATASCI
• Twitter: https://twitter.com/odsc & @odsc
• LinkedIn: https://www.linkedin.com/company/open-data-science
• Slack Channel: https://hubs.li/Q018SM1r0
• ODSC Europe 2022 June 15th-16th - https://hubs.li/Q012hpDP0
• ODSC APAC 2022 September 7th-8th - https://hubs.li/Q01bgr6W0
• Code of conduct: https://odsc.com/code-of-conduct/
This is PAID event. Pre-registration is required - https://hubs.li/Q02sx0fQ0
And get your pass to the future of AI today for less with our exclusive community discount with code: Community2024-EU
VIRTUAL PASS with Community discount is HERE
In-Person PASS with Community discount is HERE
Over the 2 days of the conference, we’ll feature 200+ hours of workshops, tutorials, talks on:
AI Agents | Mixture of Experts | AI Guardrails | RAG | Applied AI | Open Source LLMs | AI Infrastructure | Generative AI | the RAISE framework | Task Heads | Ludwig.ai | LoRAX | and much more!
If you are a data scientist, data, software, or machine learning engineer, data analyst, or AI professional, this conference is for you.
But don’t take our word for it, see what past attendees have had to say.
“[ODSC] was an amazing chance to meet new people and stay up-to-date with the latest trends in data science.” – MSc Business Analytics UCL
“Great talks, great content, and looking forward for more!” – Full Stack Data Scientist
Have questions? We can help! Contact us at info@odsc.com
ODSC Links:
• Get free access to more talks/trainings like this at Ai+ Training platform:
https://hubs.li/H0Zycsf0
• ODSC blog: https://opendatascience.com/
• Facebook: https://www.facebook.com/OPENDATASCI
• Twitter: https://twitter.com/_ODSC & @odsc
• LinkedIn: https://www.linkedin.com/company/open-data-science
• Slack Channel: https://hubs.li/Q02zdcSk0
• Code of conduct: https://odsc.com/code-of-conduct/
Próximos eventos (4)
Ver todo- Hybrid ODSC Europe 2024 | The AI Training ConferenceNovotel London West, London
This is PAID event. Pre-registration is required - https://hubs.li/Q02sx0fQ0
And get your pass to the future of AI today for less with our exclusive community discount with code: Community2024-EU
VIRTUAL PASS with Community discount is HEREIn-Person PASS with Community discount is HERE
Over the 2 days of the conference, we’ll feature 200+ hours of workshops, tutorials, talks on:
AI Agents | Mixture of Experts | AI Guardrails | RAG | Applied AI | Open Source LLMs | AI Infrastructure | Generative AI | the RAISE framework | Task Heads | Ludwig.ai | LoRAX | and much more!
If you are a data scientist, data, software, or machine learning engineer, data analyst, or AI professional, this conference is for you.
But don’t take our word for it, see what past attendees have had to say.
“[ODSC] was an amazing chance to meet new people and stay up-to-date with the latest trends in data science.” – MSc Business Analytics UCL
“Great talks, great content, and looking forward for more!” – Full Stack Data Scientist
Have questions? We can help! Contact us at info@odsc.com
ODSC Links:
• Get free access to more talks/trainings like this at Ai+ Training platform:
https://hubs.li/H0Zycsf0
• ODSC blog: https://opendatascience.com/
• Facebook: https://www.facebook.com/OPENDATASCI
• Twitter: https://twitter.com/_ODSC & @odsc
• LinkedIn: https://www.linkedin.com/company/open-data-science
• Slack Channel: https://hubs.li/Q02zdcSk0
• Code of conduct: https://odsc.com/code-of-conduct/ - Virtual Session "Tabular Learning: skrub and Foundation Models"Solo los asistentes pueden ver el enlace
To access this session, please register here: https://hubs.li/Q02MTB2L0
Topic: "Tabular Learning: skrub and Foundation Models"
Speaker: Gaël Varoquaux, PhD / Research Director | scikit-learn Author | Co-Founder / Inria | Probabl
Varoquaux's research covers fundamentals of artificial intelligence, statistical learning, natural language processing, causal inference, as well as applications to health, with a current focus on public health and epidemiology. He also creates technology: he co-funded scikit-learn, one of the reference machine-learning toolboxes, and helped build various central tools for data analysis in Python.
Varoquaux has worked at UC Berkeley, McGill, and university of Florence. He did a PhD in quantum physics supervised by Alain Aspect and is a graduate from Ecole Normale Superieure, Paris.
Abstract:
While tabular data is central to all organizations, it seems left out of the AI discussion, which has focused on images, text and sound. Ineed, for data science, most of the excitement is in machine learning, but most of the work happens before. Tables often require extensive manual transformation or "data wrangling".Gaël will discuss how they progressively rethought this process, building machine learning tool that require less wrangling. We are building a new library, skrub (https://skrub-data.org), that facilitates complex tabular-learning pipelines, writing as much as possible wrangling as high-level operations and automating them. A few lines of skrub can spare you dozens of wrangling lines!
But can more bleeding-edge research bring the revolution of fondation models? Our latest breakthrough, the CARTE model, shows how pretrained models can bring value to downstream table analytics without manually transforming these tables to please the model; maybe the begining of a large tabular model revolution.
ODSC Links:
• Get free access to more talks/trainings like this at Ai+ Training platform:
https://hubs.li/H0Zycsf0
• ODSC blog: https://opendatascience.com/
• Facebook: https://www.facebook.com/OPENDATASCI
• Twitter: https://twitter.com/_ODSC & @odsc
• LinkedIn: https://www.linkedin.com/company/open-data-science
• Slack Channel: https://hubs.li/Q02zdcSk0
• Code of conduct: https://odsc.com/code-of-conduct/ - Virtual Session "Do Large Language Models have a Duty to Tell the Truth?"Solo los asistentes pueden ver el enlace
To access this session, please register here: https://hubs.ly/Q02MKxDg0
Topic: "Do Large Language Models have a Duty to Tell the Truth?"
Speaker: Brent Mittelstadt, PhD / Associate Professor / University of Oxford
He leads the Governance of Emerging Technologies (GET) research programme which works across ethics, law, and emerging information technologies. He is a data ethicist and philosopher specializing in AI ethics, algorithmic fairness and explainability, and technology law and policy. Prof. Mittelstadt is the author of foundational works addressing the ethics of algorithms, AI, and Big Data; fairness, accountability, and transparency in machine learning; data protection and non-discrimination law; group privacy; ethical auditing of automated systems; and digital epidemiology and public health ethics. His contributions in these areas are widely cited and have been implemented by researchers, policy-makers, and companies internationally, featuring in policy proposals and guidelines from the UK government, Information Commissioner’s Office, and European Commission, as well as products from Google, Amazon, and Microsoft. He also serves on the Advisory Board of the IAPP AI Governance Centre.Abstract:
Careless speech is a new type of harm created by large language models (LLM) that poses cumulative, long-term risks to science, education, and the development of shared social truths in democratic societies. LLMs produce responses that are plausible, helpful, and confident but that contain factual inaccuracies, inaccurate summaries, misleading references, and biased information. These subtle mistruths are poised to cause a severe cumulative degradation and homogenisation of knowledge over time.This talk examines the existence and feasibility of a legal duty for LLM providers to create models that “tell the truth.” LLM providers should be required to mitigate careless speech and better align their models with truth through open, democratic processes. Careless speech is defined and contrasted with the simplified concept of “ground truth” in LLMs and prior discussion of related truth-related risks in LLMs including hallucinations, misinformation, and disinformation. EU human rights law and liability frameworks contain some truth-related obligations for products and platforms, but they are relatively limited in scope and sectoral reach.
The talk concludes by proposing a pathway to create a legal truth duty applicable to providers of both narrow- and general-purpose LLMs, and discusses “zero-shot translation” as a prompting method to constrain LLMs and better align their outputs with verified, truthful information.
ODSC Links:
• Get free access to more talks/trainings like this at Ai+ Training platform:
https://hubs.li/H0Zycsf0
• ODSC blog: https://opendatascience.com/
• Facebook: https://www.facebook.com/OPENDATASCI
• Twitter: https://twitter.com/_ODSC & @odsc
• LinkedIn: https://www.linkedin.com/company/open-data-science
• Slack Channel: https://hubs.li/Q02zdcSk0
• Code of conduct: https://odsc.com/code-of-conduct/ - LIVE TRAINING “Operationalizing AI/ML Applications on OpenShift”Solo los asistentes pueden ver el enlace
It is PAID event. You may access training with paid subscription to Ai+ training platform or purchase access to this specific session. More details are here - https://hubs.li/Q02Hp2_m0
This workshop will delve into the "FlyingThings" project, a sophisticated computer vision demo developed to demonstrate the integration of AI/ML workflows within OpenShift. Attendees will learn about deploying, training, and serving machine learning models using Nvidia GPU hardware and an array of tools from the Red Hat ecosystem and third-party applications. The session will also cover practical setup scripts, workshop instructions, and resources for advanced exploration.
Instructor's bio: David Whiteб Associate Principal Specialist Solution Architect | Red Hat
David has 20 years experience in the IT industry in a variety of roles and platforms. Having led many design/development efforts, he believes in a holistic view and approach to designing and implementing total solutions. His approach is very “hands-on'' with regard to evaluating and prototyping solutions whether it’s coding up Java applications to test API integration, developing automation scripts for “hands off” deployments, or building an entire pipeline in Amazon AWS to illustrate advanced DevOps concepts and “infrastructure as code” techniques. He is an expert in Linux, MS Windows, Mac OSX, Unix, and Virtualization platforms.ODSC Links:
• Get free access to more talks/trainings like this at Ai+ Training platform:
https://hubs.li/H0Zycsf0
• ODSC blog: https://opendatascience.com/
• Facebook: https://www.facebook.com/OPENDATASCI
• Twitter: https://twitter.com/_ODSC & @odsc
• LinkedIn: https://www.linkedin.com/company/open-data-science
• Slack Channel: https://hubs.li/Q02zdcSk0
• Code of conduct: https://odsc.com/code-of-conduct/