Recent advances in machine learning have proved to be particularly beneficial in the financial sector, helping organizations avoid loss through fraud detection and streamline their processes. To learn more about how machine learning is transforming the financial industry, check out the below ODSC Europe talks on quant finance in AI.
How to Build and Test a Trading Strategy Using ML
Stefan Jansen｜Founder & Lead Data Scientist｜Applied Artificial Intelligence
This workshop covers popular ML use cases for the investment industry. In particular, it focuses on how ML fits into the workflow of developing a trading strategy, from the engineering of financial features to the development of an ML model that generates tradable signals, the backtesting of a trading strategy that acts on these signals, and the evaluation of its performance.
Relationships Matter: Using Connected Data for Better Machine Learning
Dr. Alicia Frame｜Lead Data Scientist｜Neo4j
In this session, you will learn how to use graphs, in which relationships are embedded in the data itself, to incorporate the highly predictive capabilities of relationships into your existing practices.
Bayesian Modeling without the Math
Thomas Wiecki, PhD｜CEO｜PyMC Labs
Although user-friendly modeling packages like PyMC3 exist, understanding the concepts underlying Bayesian modeling still provides a challenge for many newcomers, particularly since not much importance is placed in intuition typically. In this talk I will take the opposite approach: throw all math out the window and explain the underlying concepts in an intuitive way.
Finding that Needle! Modern Approaches to Fraud and Anomaly Detection
Aric LaBarr, PhD｜Associate Professor of Analytics｜Institute for Advanced Analytics at NC State University
This talk will highlight some modern approaches to anomaly detection – local outlier factors, isolation forests, and classifier adjusted density estimation (CADE), all of which have foundations in places that were not originally anomaly detection, but have been shown to have great abilities to find anomalous observations in a data set.
Hands-on RL in Finance: Playing Atari VS Playing Markets
Alex Honchar｜Director Neuron｜Labs
This workshop will familiarize attendees with the mechanics of reinforcement learning (RL) applied to financial environments and uncover key differences between popular RL applications (such as playing video games) and financial ones.
Machine Learning for Economics and Finance in TensorFlow 2
Isaiah Hull｜Senior Economist｜Research Division of Sveriges Riksbank
This tutorial explores machine learning applications in economics and finance using TensorFlow 2. It will examine how TensorFlow and machine learning can be used to solve empirical and theoretical models in economics, provide an introduction to deep learning and gradient boosting for structured economic and financial datasets, discuss how to augment structured datasets with text-based features through the use of natural language processing models, and examine how generative adversarial networks can be used in simulation and estimation exercises in economics and finance.
An Introduction to Machine Learning in Quantitative Finance
Dr. Hao Ni｜Turing fellow, Associate Professor｜Alan Turing Institute, UCL
This tutorial aims to demystify ML by uncovering its underlying mathematics and showing how to apply ML methods to real-world financial data. It will start with a brief overview of machine learning in quantitative finance and then dive into supervised learning, in particular deep learning.
Register now and see all ODSC Europe quant finance in AI talks
These are just a few of the training sessions, workshops, and talks on quant finance that will be featured at ODSC Europe next month. Register now and gain access to all of the best ODSC Europe quant finance talks live and on-demand following the event. And remember – the General Pass is now free so you can see all talks for free. Training and workshops will require the All-Access Pass.