Open Data Science

Topic: "Generate Synthetic Tabular Data with GANs"Speaker: Hanhan Wu, Senior Manager of Data Science at ScotiabankAbstract:Generative AI is popular nowadays, and we have seen lots of use cases applied on image and text data. Have you ever used it on tabular data? In this talk, Hanhan is going to share her experiments and findings on generating synthetic tabular data using latest tabular generative adversarial networks (TGANs).Learning points:- Understand how does GANs work to generate synthetic data - Understand how does latest (2019 ~ 2023) TGANs work to generate tabular synthetic data - See experiments and results - A tip to improve TGANs performance on generating synthetic data - Discuss questions, your experience or thoughtsJoin ODSC Europe 2024 - The Leading AI&Data Science Training Conference - https://hubs.li/Q02sx0fQ0 Use Community2024-EU discount code

Topic: Time-Series Databases for AI: Enabling Trend Analysis, Anomaly Detection, and Accurate PredictionsSpeaker: Anais Dotis-Georgiou, Developer Advocate at InfluxDataAbstract: Real-world AI applications require time-series data to transform raw data into valuable intelligence. Time-series data, recorded chronologically, enables trend analysis, anomaly detection, and accurate predictions. This session will consider why it’s essential to look at a time series database when working with ML and AI, how they differ from other databases, and factors such as scalability, data ingestion and storage capabilities, advanced analytics support, and integration capabilities.We will also share real-life use cases of companies using the InfluxDB time series database in their production-ready environments to support predictive analytics and automation.Join ODSC Europe 2024 - The Leading AI and Data Science Training Conference this September - https://hubs.li/Q02sx0fQ0 Use Community2024-EU code for an extra discount

In this webinar, we will cover advanced techniques for leveraging the full power of Large Language Models (LLMs) while adhering to a reasonable budget. We work with many data scientists who have successfully demonstrated the potential of GenAI technology, only to find themselves encountering significant obstacles when it comes to cost and efficiency at production scale. Our session will guide attendees through innovative strategies to overcome these challenges, including:- Utilizing Small Language Models (SLMs) for efficiency - Employing LLM Distillation to reduce resource demands - Implementing prompt unit testing to maintain quality integritySpeaker: Ivan Lee, CEO of Datasaur