Temat: How to transform a notebook model into a system pipeline
Opis prelekcji: “In the world of data analysis, there is a lot of information on the Internet about building models of various kinds to solve all kinds of problems. However, when a complex model is developed, it is necessary to implement it in a software system.
In this step, most of the people dedicated to data science, need the help of software architects and engineers, MLOps, etc. Therefore, in this workshop, we intend to show the first steps to identify how to segment a model in processing stages, and implement a distributed pipeline, managed by basic continuous integration techniques, allowing the creation and maintenance of a comprehensive system that serves the model.
To do so, we will first introduce the concept of microservice architectures and event-driven architectures, and then explain what an event broker is and start working with a real one, Apache Kafka.
Once the work base is established, we will teach how to create microservices in Python integrated with Apache Kafka, with a model (or part of it) integrated in these, as well as the necessary scripts for the continuous integration of these.
Finally, we will explain the possibilities offered when integrating ingest, storage, etc. so that attendees can expand their knowledge in this area later.”
Prelekcja w języku angielskim.
Serdecznie zapraszamy – spotkanie otwarte dla wszystkich zainteresowanych!
Opis prelekcji: „Legal research is a highly manual and time-consuming process. Legal professionals, for example, have to read court cases that are up to 100 pages long, just to identify the most important aspects in order to decide whether their firm should represent the case.
Natural Language Processing (NLP) techniques like information extraction and summarisation thus provide great opportunities to save law firms time. However, applying NLP to legal documents is highly challenging due to the domain-specific terminology and variability in the legal document layout.
In this talk, we show how Thomson Reuters Labs tackles these challenges and present our work on summarising court cases and providing human-understandable explanations thereof.”
Tematem prelekcji to: Predicting the Unpredictable: Mathematical Models and the Covid 19 Pandemic
„Predicting the future of the COVID-19 pandemic is a challenging task and can not be done without mathematical models describing the progression of the epidemic.
Despite large uncertainties about epidemiological relevant medical and social key parameters, mathematical models can provide deep insights into the dependency of the epidemic dynamics on those parameters.
Epidemiological models can furthermore be used to develop and improve rational strategies for controlling the COVID-19 epidemics.
We focus in the talk on fundamental mathematical features of individual based epidemic models and highlight the close relation to problems in percolation and random graph theory.
We emphasize the special role of households and discuss some results and conjectures in first passage percolation and their impact on epidemic processes.
Finally we present some outcomes of the MOCOS microsimulation model for the COVID -19 epidemic in Poland and Germany and reflect on problems related to model based policy advice for epidemic control.”
Temat prelekcji to: „Rzeczywistość projektów Data Science”
Parę słów od Prelegenta:
„W oparciu o doświadczenia deepsense.ai z blisko 100 zrealizowanych projektów z zakresu analizy danych i uczenia maszynowego, przybliżymy napotykane wyzwania i problemy, które rzadko przypominają te z konkursów Kaggle’a.”