Explainable AI (xAI) is a hot topic today. We have seen a boom in AI, because deep learning methods made a huge difference in many cases. There are also many more use cases of AI compared to times before Deep Learning was introduced. The problem that we face now is that many methods work and we believe that whatever is done under the hoods, we don’t elaborate about the details. The reality is that it's very important to understand the way the prediction is done and not only understand the architecture of the method. There are many scenarios where xAI is very useful. During the talk we explain the xAI methods with a focus on medtech, fintech cases

WebAssembly (Wasm) is a binary instruction format for a stack-based virtual machine. Wasm enables developers to use existing code libraries (e.g. C/C++, Rust) as part of their application development process. Wasm is not just for the web and today moves in exciting new directions. One primary use-case would be to run a Machine Learning algorithm directly in a database system on the data already stored in the database system -- an example of co-locating analytics with data. Attendees will learn how we can use an ML classifier and then port the code to a Wasm module. No prior knowledge or experience of Wasm is required. Wasm standards are being developed by the W3C and actively promoted through non-profit organisations such as the Bytecode Alliance.

Dialogflow CX is the new product launched by Google for creating bots. In this talk, I will show you how it works and what you need to develop your bots with this cutting-edge technology! We will review how the AI works with this technology, the Natural Language Understanding, and everything related to the bot backend using Google Serverless. Be ready for the next-gen Cloud Conversational AI from Google! We will talk about ChatGPT, GPT-4, Large Language Models, and prompt chaining techniques as well.

This will focus on applications of algorithms for commonly seen retail ads, targeted campaigns with a deep dive on audience segmentation with k-means algorithm. Lifetime Value Prediction, Audience Segmentation and other algorithms are often used in Retail brick and mortar shops as well as e-commerce. We will understand the commonly used ML algorithms and the theory behind clustering algorithms, when to use them too. Further we will go through best practices for implementing such ML algos in scale in real world scenarios. We will also discuss what different roles exist in the data science field.

Data can be powerful, meaningful, AND fun. Making data-driven decisions can level up your family vacation from awful to awesome. In this session, attendees will walk through a specific example showing how to analyze various data sources to avoid crowds, save money, and piece together a Disney World vacation that's more enjoyable for everyone. Then, they will learn through this fun example how they can follow a repeatable framework to apply data science to many different problem sets, and effectively communicate the results to non-technical users.