We are delighted to announce our Europe 2023 Preliminary Schedule!
90+ Additional Sessions Coming Soon
All sessions are scheduled in GMT time zone (UK time zone)
- ODSC Talks schedule includes Wednesday, June 14th – Thursday, June 15th. In-person sessions are available to Platinum and Mini-Bootcamp pass holders. Virtual Sessions are available to Virtual Premium, Virtual Platinum & Virtual Mini-Bootcamp pass holders.
- ODSC Trainings are scheduled from June 14th – Thursday, June 15th. In-person sessions are available to Platinum & Mini-Bootcamp Pass holders. Virtual Sessions are available to Virtual Platinum & Virtual Mini-Bootcamp pass holders.
- ODSC Workshop/Tutorials are scheduled from June 14th to Thursday, June 15th. All in-person sessions are available to Platinum & Mini-Bootcamp holders. Virtual Sessions are available for Virtual Premium, Virtual Platinum & Virtual Mini-Bootcamp pass holders.
- ODSC Bootcamp Sessions are scheduled VIRTUALLY on Tuesday, June 13 as pre conference training. They are ONLY available for In person Mini-Bootcamp, and VIP Pass and Virtual Mini-Bootcamp holders.
Speaker and speaker schedule times are subject to change.
Please Note: In-Persons attendees will have access to virtual sessions. If you have a virtual Pass, please note that we will not live-stream any in-person sessions. Only virtual sessions will be recorded.
Virtual | Bootcamp | Beginner
In this class students will install Anaconda Python and Jupyter Labs. Using this Jupyter Lab interface I will cover the basics of Python programming. Topics will include built in data structures, functions, looping, decisions, and importing other libraries…more details
In-person | Bootcamp | Machine Learning | Beginner
In this workshop, you will get acquainted with the pandas library, which is the most widely used package for reading, analyzing and exporting datasets in Python. You will also learn how to visualize many kinds of tabular data using the plotnine package, along with some tips and tricks on how to make your visualizations stand out. Lastly, you will have the opportunity make predictions and take decisions using data, based on basic statistical methods…more details
Virtual | Talk | NLP | Machine Learning | Deep Learning | Generative AI | All Levels
In this talk, I will first introduce the field of semantics and the task of semantic analysis, a.k.a, semantic parsing from a multilingual perspective. In particular, we will first discuss the layers of meaning, from morphology to pragmatics, and then define the scope of semantics as a field…more details
In-person | Talk | NLP | Machine Learning | Intermediate
In this talk, I will first give an overview of the built-in functionality available in spaCy, using pretrained models. I will showcase how linguistic information such as part-of-speech tags and dependency parses can help you identify interesting patterns or phrases in your documents and ultimately perform document classification or other information retrieval tasks…more details
Virtual | Business Talk | Cross Industry | Intermediate
On average, most generative models are truthful only 25% of the time, according to Stanford Artificial Intelligence Index Report 2022 . The downstream impact is not just limited to ML or business teams as it trickles down to the end customer who faces the first-hand repercussions of inaccurate and incorrect predictions. With the adoption of AI Observability tools, pioneering tech giants have managed to quickly catch model issues, diagnose root causes, and perform continuous improvement to optimize the model’s performance…more details
In-person | Talk | Machine Learning | Deep Learning | NLP | Beginner-Intermediate
During the talk, we’ll show how Ludwig’s novel compositional model architecture referred to as encoder-combiner-decoder makes it possible to easily mix multiple modalities of data such as text, images, audio with structured data in a way that is consistently easy across tasks like regressions, classification, and even generation…more details
Virtual | Talk | Machine Learning | Deep Learning | Intermediate
A common problem in the cybersecurity industry is how to detect and track botnets when there are billions of daily attacks. Botnets are internet connected devices that perform repetitive tasks, such as Distributed Denial of Service (DDoS). In many cases, these consumer devices are infected with malicious malware that is controlled by an external entity, often without the owner’s knowledge…more details
In-person | Talk | MLOps & Data Engineering | Responsible AI | Beginner
From this talk you will learn:
– What ML Governance is meant to achieve
– How to get started with a template process
– The role of documentation (and especially Google Model Cards)
– Which roles have what responsibilities
– The relevance of a governance board
Virtual | Talk | Machine Learning for Finance | All Levels
The principal component analysis (PCA) is a staple statistical and unsupervised machine learning technique in finance. The application of PCA in a financial setting is associated with several difficulties, such as numerical instability and nonstationarity. We attempt to resolve them by proposing two new variants of PCA: an iterated principal component analysis (IPCA) and an exponentially weighted moving principal component analysis (EWMPCA). Both variants rely on the Ogita-Aishima iteration as a crucial step…more details
In-person | Talk | Machine Learning | Deep Learning | Intermediate
In this session, we’ll explore and discuss the following:
– Why and what is Ray
– How AIR, built atop Ray, allows you to program and scale your machine learning workloads easily
– AIR’s interoperability and easy integration points with other systems for storage and metadata needs
– AIR’s cutting-edge features for accelerating the machine learning lifecycle such as data preprocessing, last-mile data ingestion, tuning and training, and serving at scale..more details
In-person | Talk | Machine Learning | Machine Learning Safety and Security | Data Engineering & Big Data | Responsible AI | Intermediate
If you’ve ever asked one of the questions above, then this talk is for you! You’ll learn how the ability to interpret a model can identify poor model performance or, worse, bias that could ultimately impact the fairness of your machine learning applications. You’ll learn about some of the most common algorithms, how they work and how you can get started using them yourself…more details
Virtual | Talk | Machine Learning for Finance | Intermediate
The objective of this session is to make attendees familiar with the reasons why probabilistic machine learning is the next generation of AI in finance and investing…more details
Virtual | Talk | Responsible Ai | Machine Learning | Beginner
This talk will introduce the audience to challenges in AI for health equity with a particular focus on race and ethnicity data. We will explore real-world ethnicity data collected routinely in healthcare settings in the form of electronic health records. We will examine issues with completeness, correctness, and granularity of these data, implications for healthcare AI, and finally highlight opportunities towards “better data, better models, better healthcare”…more details
In-person | Talk | Generative AI | Machine Learning, Deep Learning | All Levels
The session will cover the importance of explaining AI models and their limitations, building effective next-gen data products, evaluating audience and user needs, and the aspects of visualisation that will always require human input. It will focus on the practical implications of AI tools on the roles of data professionals – and look at how we can thrive in this exciting new era…more details
In-person | Talk | Machine Learning for Finance
In this talk, we will look at how deep learning techniques can be used for building fast option pricers. A large set of representative training data is generated by using the numerical pricers. Then deep neural networks are used to learn the non-linear pricing functions…more details
In-person | Talk and Career Talk
In this lightning overview, we’ll discuss the most impactful changes you can make to your data science practice. Topics include running a model in shadow mode, data versioning, estimating costs, and communicating impact to a non-technical audience…more details
In-person | Workshop | Machine Learning | Deep Learning | Intermediate
In this workshop we will illustrate both approaches using a consistent single example. We will use TensorFlow in a Colab notebooks, so all you need is a recent version of Chrome and a Google login. You will not need prior knowledge with TensorFlow, but need a good understanding of how training neural networks work as a prerequisite…more details
In-person | Tutorial | Generative AI | Machine Learning | Deep Learning | NLP | Intermediate-Advanced
In the first part of the talk I will provide an overview of the latest generative AI models and how they work. This will include discussing the various types of generative AI models, such as diffusion models for image generation and transformer (GPT-like) models for text generation and their underlying architectures and key concepts…more details
In-person | Half-Day Training | Machine Learning for Finance | Intermediate
This half-day trading session covers the most important Python topics and skills to apply AI and Machine Learning (ML) to Algorithmic Trading. The session shows how to make use of the Oanda trading API (via a demo account) to retrieve data, to stream data, to place orders, etc. Building on this, a ML-based trading strategy is formulated and backtested. Finally, the trading strategy is transformed into an online trading algorithm and is deployed for real-time trading on the Oanda trading platform…more details
