BIG DATA CONFERENCE

EUROPE 2022

November 23-24

Online

Confirmed Talks

Antía Fernández

Gradiant, Spain

Big or Small Data in the Food Industry?

In this session, Antia Fernandez will talk about different applications of artificial intelligence for the food sector Gradiant clients. As an introduction type of data from the company (sensors, business and people) and what we do in a generic way to extract more business value will be presented.

Session Keywords
🔑 Big Data
🔑 Data Analytics
🔑 Food Industry

Ibrahim Muzaferija

Maestral Solutions, Bosnia & Herzegovina

Cloud Computing Anomaly and Threat Detection Using Big Data Analytics and Machine Learning

While leveraging cloud computing for large-scale distributed applications allows seamless scaling, many companies struggle to follow up with the amount of data generated in terms of efficient processing and anomaly detection. With the rapid growth of web attacks, anomaly detection becomes a necessary part of the management of modern large-scale distributed web applications.

Session Keywords
🔑 Cloud
🔑 ML
🔑 Anomaly Detection
🔑 Support Vector Machines
🔑 User Behavior Modeling

Clodéric Mars

AI Redefined, Canada

Towards Human-AI Teaming: Challenges and Opportunities of Human in the Loop AI Training

The goal of our presentation is to stress the need for Human-in-the-Loop and Hybrid-Systems based thinking in AI driven systems. We present solutions with experimental results to formulate and implement such systems. During the session you will hear about the distributing learning processes to build automated AI systems, find out how to ensemble created models to accelerate next-level training processes as well as listen about the architecting communication to facilitate human-AI interactions.

Session Keywords
🔑 ML
🔑 Multi-Agent Systems
🔑 Reinforcement Learning

Sagar Kurandwad

AI Redefined, Canada

Clodéric Mars

AI Redefined, Canada

Sagar Kurandwad

AI Redefined, Canada

Towards Human-AI Teaming: Challenges and Opportunities of Human in the Loop AI Training

The goal of our presentation is to stress the need for Human-in-the-Loop and Hybrid-Systems based thinking in AI driven systems. We present solutions with experimental results to formulate and implement such systems. During the session you will hear about the distributing learning processes to build automated AI systems, find out how to ensemble created models to accelerate next-level training processes as well as listen about the architecting communication to facilitate human-AI interactions.

Session Keywords
🔑 ML
🔑 Multi-Agent Systems
🔑 Reinforcement Learning

Ben Herzberg

Satori, Israel

DataSecOps: Why You Should Care

In this session we will discuss DevOps and the transition to DevSecOps, and what we can do better (as an industry) when it comes to embedding security in DataOps.

Session Keywords
🔑 Cloud
🔑 DataOps
🔑 Security
🔑 Data Engineering

Diana Gabrielyan

Stockmann, Finland

Machine Learning Helping the Economy

Machine learning is a catalyst for productivity growth. In the near future, many current jobs and tasks will be performed totally by machine learning and Artificial Intelligence algorithms or with the usage of them. According to PWC, machine learning in economics can increase productivity by up to 14.3% by 2030.

Session Keywords
🔑 ML
🔑 Text Mining
🔑 Economics
🔑 Inflation

Federico Fregosi

Contino, UK

Architecture vs. Operating Model – A Cloud Conundrum

In this talk, we will cover our experience liberating the data in the mainframe with a hybrid serverless/containerized solution built on AWS. We will dedicate a special section to performance optimizations done to reduce the cold start problems and support aggressive performance targets.

Session Keywords
🔑 Mainframe
🔑 Serverless
🔑 Data Streaming

Kathrin Melcher

Knime, Germany

A Friendly Introduction to Codeless Deep Learning

In this talk, you’ll first get a basic introduction to neural networks, the concepts behind training them, and how to build and train a DL model without needing a single line of code using the Keras integration of the KNIME Analytics Platform. Once you are familiar with the basics we will move on to convolution neural networks, for image processing.

Session Keywords
🔑 Deep Learning
🔑 CNN
🔑 Keras
🔑 KNIME

Paweł Skrzypek

AI Investments, Poland

Anna Warno

AI Investments, Poland

Complex AI Forecasting Methods for Investments Portfolio Optimization

Presentation of the first complete AI investment platform. It is based on the most innovative AI methods: most advanced neural networks (ResNet/DenseNet, LSTM, GAN autoencoders) and reinforcement learning for risk control and position sizing using the Alpha Zero approach.

Session Keywords
🔑 ML
🔑 Forecasting
🔑 Investing

Paweł Skrzypek

AI Investments, Poland

Complex AI Forecasting Methods for Investments Portfolio Optimization

Presentation of the first complete AI investment platform. It is based on the most innovative AI methods: most advanced neural networks (ResNet/DenseNet, LSTM, GAN autoencoders) and reinforcement learning for risk control and position sizing using the Alpha Zero approach.

Session Keywords
🔑 ML
🔑 Forecasting
🔑 Investing

Anna Warno

AI Investments, Poland

Valentina Djordjevic

Things Solver, Serbia

Building Data Science Products

She will be talking about the challenges in building this kind of platform, switching from service-oriented data science teams to product-oriented teams, changing the mindset, biggest problems encountered, and how we managed to tackle growth, client pressure, data science, heuristics, and algorithms under the same umbrella.

Session Keywords
🔑 ML
🔑 Data Science
🔑 Product Development