2.0 -//Pentabarf//Schedule//EN PUBLISH GMKHFE@@pretalx.com -GMKHFE Garbage in -> Pydantic -> you're golden! en en 20230518T093000 20230518T103000 010000

Garbage in -> Pydantic -> you're golden!

In this talk I'll give a brief introduction to Pydantic, what it can do and how it differs from other similar libraries. I'll then go on to walk through an example of how Pydantic can be used to prepared data to train a machine learning model, including some advantages of Pydantic over dataclasses or regular dictionaries. Finally I'll give a high level introduction to how Rust is being used to build python extensions, and why that's (mostly) a great thing for the community and the planet. The two main case studies will be the recent [re-write of Pydantic in Rust for V2](https://docs.pydantic.dev/blog/pydantic-v2/), and [Polars](https://www.pola.rs/). PUBLIC CONFIRMED Keynote https://pretalx.com/pycon-lt-2023/talk/GMKHFE/ Saphire ABC Main Samuel Colvin PUBLISH XHGK7V@@pretalx.com -XHGK7V Company presentations en en 20230518T160000 20230518T161500 001500

Company presentations

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/XHGK7V/ Saphire ABC Main PUBLISH NZD3ZB@@pretalx.com -NZD3ZB Lightning talks en en 20230518T161500 20230518T163000 001500

Lightning talks

PUBLIC CONFIRMED Lightning talk session https://pretalx.com/pycon-lt-2023/talk/NZD3ZB/ Saphire ABC Main PUBLISH 7CZQYE@@pretalx.com -7CZQYE Python and Creativity (An Explorers Guide) en en 20230518T163000 20230518T173000 010000

Python and Creativity (An Explorers Guide)

PUBLIC CONFIRMED Keynote https://pretalx.com/pycon-lt-2023/talk/7CZQYE/ Saphire ABC Main Marlene Mhangami PUBLISH VZ8BPR@@pretalx.com -VZ8BPR Code More, Draw Less: Auto-Generate Software Architecture Visualizations ft. Graph DBs, pandas & Python en en 20230518T110000 20230518T112500 002500

Code More, Draw Less: Auto-Generate Software Architecture Visualizations ft. Graph DBs, pandas & Python

Before I dive into how to make "auto-generative software architecture visualizations," let's first see if you have been in any of the following situations: 1. You often wonder before you go to sleep, "A short time ago in a galaxy far, far away, I updated my team’s arch. diagram. So why is it stale… again?" 2. Your team grew multifold over the pandemic and so did your components and ownership. Has it become harder to onboard new engineers due to the ever-changing arch. diagrams, dependencies, and owners? 3. Your new release didn't go as planned because something broke in your new code. Wouldn’t it help if you had a holistic and interactive view to navigate between components while understanding how they communicate with each other? When was the last time you used your arch. diagram as a debugging tool? 4. You managed to draw the data-flow diagram and you thought “this is majestic work right here!” But the feedback you received was, "it’s too detailed" or "it’s not detailed enough." While you’re trying to figure out the fine line between details, your hairline is starting to show! If you’ve fallen victim to any of these scenarios, behold! Your prayers have been answered! In the first half of the talk, we’ll describe an approach that can automatically identify the software design and data flows within the system. To achieve this, we use algorithmic scrapers and metadata profiling techniques that integrate with distributed trace, code structure, language dependencies, contribution ownerships, and other sources to avoid the toil of manual updates of software architecture diagrams. In the second part of the talk, we will dive deeper into the details of how to use Python data engineering libraries to enrich the collected data and process it to store it in the graph database. The graph structure not only signifies the relationship between components in a real-world manner, but also helps in generating multiple views of the software architecture in an easy and comprehensible fashion. Now, instead of the architecture and data flow diagram being a static JPEG, those auto-generative views can be compiled into interactive and immersive UIs. My team built this tool for our organization, Bloomberg, but the approach we took is germane to all tech organizations. We want to share the challenges and lessons we learned during our journey to help you build a similar tool for your organization because why not “Code More, Draw Less”?! PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/VZ8BPR/ Saphire A - Python Deleted User Kang Min Bae PUBLISH MBC3A7@@pretalx.com -MBC3A7 Domain Driven Design Meets Infractucture from Code: An AWS Credentials Management Case Study en en 20230518T113000 20230518T115500 002500

Domain Driven Design Meets Infractucture from Code: An AWS Credentials Management Case Study

Sources about Infrastructure from Code: 1. Jeremy Daly at re:Invent 2022 https://www.youtube.com/watch?v=RmwKBPCo7o4 2. Asher Sterkin at PyCon France 2023 https://www.youtube.com/watch?v=YB0UhznStlg Details of the AWS credentials management task: https://medium.com/@barbara.toporowska/iam-credentials-janitor-fa0ca3337284 PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/MBC3A7/ Saphire A - Python Barbara Toporowska PUBLISH AYMGYQ@@pretalx.com -AYMGYQ H2O Wave - Build web apps with nothing but Python en en 20230518T120000 20230518T122500 002500

H2O Wave - Build web apps with nothing but Python

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/AYMGYQ/ Saphire A - Python Martin Turóci PUBLISH S3DXDJ@@pretalx.com -S3DXDJ I talk to ChatGPT about things en en 20230518T140000 20230518T142500 002500

I talk to ChatGPT about things

Quick introduction to Large Language Models, how they are trained and what can be improved. Slides and examples of the test associated with ChatGPT. Discussion of why ChatGPT fails with understanding contexts, doesn't do well at verbal math, doesn't know what a venn diagram is and has never heard an egg crack and what it means for the next generation of a conversational AI model. PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/S3DXDJ/ Saphire A - Python Aroma Rodrigues PUBLISH JVLY8S@@pretalx.com -JVLY8S Market attribution in an increasingly privacy-centric industry en en 20230518T143000 20230518T145500 002500

Market attribution in an increasingly privacy-centric industry

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/JVLY8S/ Saphire A - Python Avision Ho PUBLISH B8RYGN@@pretalx.com -B8RYGN Mercury widgets - a new way to make interactive webapp from Jupyter Notebook en en 20230518T150000 20230518T152500 002500

Mercury widgets - a new way to make interactive webapp from Jupyter Notebook

Have you ever wanted to share Jupyter Notebook with non-technical users? Mercury is a new way to add widgets to a notebook and share it with non-programmers. You can easily build a dashboard, reports, web app, interactive slides, or REST API. Mercury allows you to add widgets to Jupyter Notebook. After the widget change, all cells below the widget are reexetuted with a new widget value. This simple execution model allows converting any Jupyter Notebook into an interactive web application. You can easily create a dashboard or presentation (slides in presentations can be recomputed during the show with values provided with widgets). What is more, Mercury allows schedule automatic execution easily. The framework has a built-in authentication module so that notebooks can be shared publicly or restricted with a password. Mercury is an open-source framework. PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/B8RYGN/ Saphire A - Python Piotr Płoński Aleksandra Plonska PUBLISH 9L3HTX@@pretalx.com -9L3HTX How to Build a Data Science Portfolio That Will Make Recruiters Swipe Right en en 20230518T110000 20230518T112500 002500

How to Build a Data Science Portfolio That Will Make Recruiters Swipe Right

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/9L3HTX/ Saphire B - PyData Karolina Griciunė PUBLISH WUWM9J@@pretalx.com -WUWM9J How we predict purchases in mobile games en en 20230518T113000 20230518T115500 002500

How we predict purchases in mobile games

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/WUWM9J/ Saphire B - PyData Dima Savostyanov PUBLISH DQBWQ9@@pretalx.com -DQBWQ9 pandas 2.0 and the Arrow revolution en en 20230518T120000 20230518T122500 002500

pandas 2.0 and the Arrow revolution

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/DQBWQ9/ Saphire B - PyData Marc Garcia PUBLISH KCRSMY@@pretalx.com -KCRSMY Serverless billion-scale vector search for AI applications en en 20230518T140000 20230518T142500 002500

Serverless billion-scale vector search for AI applications

This talk will: 1. Introduce LanceDB and show some example workflows 2. Outline Lance format design and what makes it so fast 3. Review the Lance roadmap and ecosystem integrations You can find Lance here: https://github.com/eto-ai/lance PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/KCRSMY/ Saphire B - PyData Chang She PUBLISH 77ZQHE@@pretalx.com -77ZQHE Let them explore! Building interactive, animated reports in Streamlit with ipyvizzu & a few lines of Python en en 20230518T143000 20230518T145500 002500

Let them explore! Building interactive, animated reports in Streamlit with ipyvizzu & a few lines of Python

It's great when you can share the results of your analysis not only as a presentation but as something that non-data scientists can explore on their own, looking for insights and applying their business expertise to understand the significance of what they find. With its accessibility for both creators and viewers, Streamlit offers a brilliant platform for data scientists to build and deploy data apps. Now, with the integration of [ipyvizzu](https://ipyvizzu.com) - a new, open-source data visualization tool focusing on animation and storytelling - you can quickly create and publish interactive, animated reports and dashboards on top of static or dynamic data sets and your models. In this talk, one of the creators of ipyvizzu shows how their technology works within Streamlit and the advantages of using animation in self-service data exploration to help business stakeholders feel smarter and do a better job. PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/77ZQHE/ Saphire B - PyData Peter Vidos PUBLISH RKXRHP@@pretalx.com -RKXRHP Polars: done the fast, now the scale en en 20230518T150000 20230518T152500 002500

Polars: done the fast, now the scale

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/RKXRHP/ Saphire B - PyData Ritchie Vink PUBLISH KAJGPU@@pretalx.com -KAJGPU Analyze your data at the speed of light with Polars and Kedro en en 20230518T110000 20230518T115500 005500

Analyze your data at the speed of light with Polars and Kedro

In this workshop we present Kedro, an opinionated Python framework for creating reproducible, maintainable and modular data science code. We will also show how you can combine it with Polars, a new dataframe library backed by Arrow and Rust, for lightning fast data manipulation and exploratory data analysis. Kedro is an open source (Apache 2.0) Python framework for maintainable data science that provides a series of project templates, a declarative data catalog, functionality to create function-based data pipelines, and a powerful visualization tool. It has a rich ecosystem of plugins and extensions and a thriving community. Traditionally, Kedro has encouraged the use of pandas for data I/O and manipulation. In recent times, Polars has become increasingly popular thanks to its expressive API, its lazy evaluation system, its out of core capabilities, and its impressive performance. The workshop will be hands on, and the outline is as follows: 1. The problem of maintainability in data science code 2. What is Kedro? 3. Quick data I/O with Polars 4. Introducing the Kedro catalog and the Jupyter integration 5. Creating pipelines in Kedro 6. More exploratory data analysis with Polars 7. Plots in Kedro Viz PUBLIC CONFIRMED Workshop https://pretalx.com/pycon-lt-2023/talk/KAJGPU/ Saphire C - Web Dev Juan Luis Cano Rodríguez PUBLISH 3BQCJW@@pretalx.com -3BQCJW Streamlit meets WebAssembly - stlite en en 20230518T140000 20230518T142500 002500

Streamlit meets WebAssembly - stlite

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/3BQCJW/ Saphire C - Web Dev Yuichiro Tachibana PUBLISH ZCBFAD@@pretalx.com -ZCBFAD HTMX vs WASM - more backend or more frontend? en en 20230518T143000 20230518T145500 002500

HTMX vs WASM - more backend or more frontend?

In the first half of the talk we would explore the history of WASM and the Iodide project, what they enable and the closing of the Iodide project. Then we will talk about the rise of the Pyodide project and what this project enables - including another popular framework - PyScript. There will be some quick code demo of both Pyodide and PyScript. In the second half of the talk, we will switch our attention to HTMX, what's the idea behind it and how it can be used to access AJAX, CSS Transitions, WebSockets and Server-Sent Events directly in HTML. There will also be some code demos of how to use HTMX, especially using it together with Django. In the last part of the talk, there will be a conclusion, do we want more backend or more frontend? And most importantly, will web developers ever need to write JavaScript anymore? PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/ZCBFAD/ Saphire C - Web Dev Cheuk Ting Ho PUBLISH P9ZKQQ@@pretalx.com -P9ZKQQ Building Hexagonal Python Services en en 20230518T110000 20230518T122500 012500

Building Hexagonal Python Services

In nearly all web applications and Python tutorials we are starting from installing a web framework, and database server, the next step is to build database models and then use ORM, etc. But wait, there is a problem with this classical approach, we lose the core business domain discussions - so-called core domain models just get lost inside some classes and functions. How about changing and reverting our approach? How about first starting by thinking, modeling our business, and core domain, and then testing it properly? Afterward, how about adding an abstraction layer on the database, then adding another abstraction on actual services, and use cases? But wait, how we are going to manage all transactional usage - okay let's add another layer with the Unit of Work pattern to manage our work as units. Sounds cryptic? Here is a step-by-step guide to starting our project: * We are going to start with domain modeling and adding tests for our domain models * The database layer will be abstracted using a Repository pattern * The database transactions will be managed by the Unit of Work pattern * The business logic actions were encapsulated in the Use Cases The question can arise: where are our web framework and database server? Answer: good architecture lets us defer those choices until the end. Because the web framework and the database server are details for our business/core application itself. Web framework will be considered as an entry point for our application and the database layer will be encapsulated using SQLAlchemy ORM, but still, ORM itself is hidden behind Repository and UoW patterns. This allows us to change the ORM library if there will be any need in the future. The most important part here is to understand how we are going to build our application using Ports and Adapters(Hexagonal) pattern and all aforementioned patterns will be divided into Ports(using abstract base classes) and Adapters(the actual implementations), we can think about this as a contract between our actual implementations and abstractions. PUBLIC CONFIRMED Workshop https://pretalx.com/pycon-lt-2023/talk/P9ZKQQ/ Coral B - Workshop Shahriyar Rzayev PUBLISH 7RVFFJ@@pretalx.com -7RVFFJ Uncle Data session 1 en en 20230518T111000 20230518T113500 002500

Uncle Data session 1

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/7RVFFJ/ Malachite A Samuel Colvin Uncle Data PUBLISH MU378T@@pretalx.com -MU378T Uncle Data session 2 en en 20230518T121500 20230518T124000 002500

Uncle Data session 2

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/MU378T/ Malachite A Justinas Kuizinas Uncle Data PUBLISH 9DMMRE@@pretalx.com -9DMMRE Uncle Data session 3 en en 20230518T140000 20230518T142500 002500

Uncle Data session 3

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/9DMMRE/ Malachite A Marc Garcia Ritchie Vink Uncle Data PUBLISH JWVUYN@@pretalx.com -JWVUYN Bayes in Business: Transparent and Interpretable Solutions en en 20230519T093000 20230519T103000 010000

Bayes in Business: Transparent and Interpretable Solutions

PUBLIC CONFIRMED Keynote https://pretalx.com/pycon-lt-2023/talk/JWVUYN/ Saphire ABC Main Dr. Thomas Wiecki PUBLISH JF3BWF@@pretalx.com -JF3BWF Company presentations 2 en en 20230519T160000 20230519T161500 001500

Company presentations 2

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/JF3BWF/ Saphire ABC Main PUBLISH XPNVC8@@pretalx.com -XPNVC8 Building sustainable software for AI and ML with lessons from the SciPyData community en en 20230519T163000 20230519T173000 010000

Building sustainable software for AI and ML with lessons from the SciPyData community

PUBLIC CONFIRMED Keynote https://pretalx.com/pycon-lt-2023/talk/XPNVC8/ Saphire ABC Main Travis Oliphant PUBLISH FYLU78@@pretalx.com -FYLU78 ML model serving and monitoring with FastAPI en en 20230519T110000 20230519T112500 002500

ML model serving and monitoring with FastAPI

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/FYLU78/ Saphire A - Python Monika Venčkauskaitė PUBLISH SRVAMA@@pretalx.com -SRVAMA One Platform for All: A Revolution for Customers, Developers, and Sales en en 20230519T113000 20230519T115500 002500

One Platform for All: A Revolution for Customers, Developers, and Sales

In a multi-product company it is not uncommon to encounter difficulties managing users: each user has a unique identity, password, and configuration across various regions and products. The customers struggle to keep track of multiple login credentials and manage their users, while engineers have to duplicate code with custom adjustments to each product; Furthermore, cross-sells are less efficient. A platform can assist to solve those problems, improve security, increase developer efficiency and enhance customer experience. I will share the process of creating a platform, including the challenges we faced and lessons learned from building it twice until we finally accomplished our goals. How we used IDP to enforce security settings, how we migrated the users and how we used it to create new revenue streams. PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/SRVAMA/ Saphire A - Python Hila Israeli PUBLISH NFKECX@@pretalx.com -NFKECX Repid: new job scheduler with Asyncio in mind en en 20230519T140000 20230519T142500 002500

Repid: new job scheduler with Asyncio in mind

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/NFKECX/ Saphire A - Python Aleksandr Sulimov PUBLISH RDUSCZ@@pretalx.com -RDUSCZ The role and skills of the developer: Past and Future en en 20230519T150000 20230519T152500 002500

The role and skills of the developer: Past and Future

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/RDUSCZ/ Saphire A - Python Robert Hoffmann PUBLISH FQHQTG@@pretalx.com -FQHQTG Driving down the Memray lane - Profiling your data science work en en 20230519T110000 20230519T112500 002500

Driving down the Memray lane - Profiling your data science work

## Goal This talk is for data scientists, learners or anyone who is interested in memory profiling their Python program. Although the talk will be using a data science use case as an example, the explanation and the tool can be expanded to be used in any Python program. However, for data science practitioners and learners who have been using Python to process data, this may be a step forward for them to improve their data workflow and prevent memory leaks from their programs. ## Outline - Introduction (5 mins) - Why we need a special tool for memory profiling (5 mins) - How to use Memray in Jupyter notebook (5 mins) - Demonstration for using Memray in data science work (5 mins) - How to interpret a frame diagram (5 mins) - Conclusion (5 mins) PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/FQHQTG/ Saphire B - PyData Cheuk Ting Ho PUBLISH D8S8NW@@pretalx.com -D8S8NW Make your first open source contribution en en 20230519T113000 20230519T115500 002500

Make your first open source contribution

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/D8S8NW/ Saphire B - PyData Marc Garcia PUBLISH BVHV3U@@pretalx.com -BVHV3U Is it the end for Apache Airflow? en en 20230519T120000 20230519T122500 002500

Is it the end for Apache Airflow?

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/BVHV3U/ Saphire B - PyData Tomas Peluritis PUBLISH EMJJ7R@@pretalx.com -EMJJ7R Production ready Machine Learning pipelines using ZenML for MLOps management en en 20230519T140000 20230519T142500 002500

Production ready Machine Learning pipelines using ZenML for MLOps management

MLOps tools today are dime a dozen, but do you really need everything to build your machine learning pipelines? In this talk, I will introduce you to the general concept of MLOps and then focus on a super interesting MLOps framework in Python called ZenML. ZenML helps you structure your code and pipelines systematically right from the word go, ensuring that you are always building pipelines that can be easily deployed in production. I will take you through the many concepts (steps, pipelines, stacks,integrations) used by ZenML and how you could use them to build your production ready Machine Learning pipelines. Though the structure is tentative, I intend to follow the following order: 1. Introduction to MLOps 2. MLOps Lifecycle 3. Introduction to ZenML concepts 4. ZenML Architecture 5. ZenML pipeline creation 6. Switching stacks to deploy a machine learning pipeline to production 7. Question and Answers PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/EMJJ7R/ Saphire B - PyData Imaad Mohamed Khan PUBLISH L8NCDS@@pretalx.com -L8NCDS MLOps Fundamentals or What Every Machine Learning Engineer Should Know en en 20230519T143000 20230519T145500 002500

MLOps Fundamentals or What Every Machine Learning Engineer Should Know

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/L8NCDS/ Saphire B - PyData Aurimas Griciunas PUBLISH C3RGAM@@pretalx.com -C3RGAM Portable Feature Engineering with Hamilton: Write Once, Run Everywhere en en 20230519T150000 20230519T152500 002500

Portable Feature Engineering with Hamilton: Write Once, Run Everywhere

In this talk, we present Hamilton, and talk about how it can enable data scientists to build highly portable dataflows that can run in a variety of different contexts. At a high level, we will discuss: The paradigm Hamilton introduces, and how it is simplifies the process of building and maintaining feature engineering pipelines How Hamilton can be used to help scale batch data preparation for training and inference How the same hamilton code can be used in a web-service to prepare data and run live inference, with minimal changes We will go over working code examples, making sure to connect with tooling people are familiar with (E.G. airflow, fastapi, metaflow, django). PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/C3RGAM/ Saphire B - PyData Elijah ben Izzy PUBLISH WNRNXP@@pretalx.com -WNRNXP How to scale old Django apps for free en en 20230519T113000 20230519T115500 002500

How to scale old Django apps for free

Django usually is considered slow and bad at doing concurrency because of its synchronous by default nature, but what if you could make it “async” without rewriting all of your codebase? Ever heard of green threads? PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/WNRNXP/ Saphire C - Web Dev Anas El Amraoui PUBLISH 8EGBPK@@pretalx.com -8EGBPK Largest B2B pharma marketplace online: 7 years effors redone in a year thanks to python en en 20230519T140000 20230519T142500 002500

Largest B2B pharma marketplace online: 7 years effors redone in a year thanks to python

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/8EGBPK/ Saphire C - Web Dev Tadas Pikutis PUBLISH GJDJEX@@pretalx.com -GJDJEX Robyn: A fast async Python web framework with a Rust runtime en en 20230519T143000 20230519T145500 002500

Robyn: A fast async Python web framework with a Rust runtime

With the rise of Rust bindings being used in the Python ecosystem, we know that throughput efficiency is one of the top priority items in the Python ecosystem. Inspired by the extensibility and ease of use of the Python Web ecosystem and the increase of performance by using Rust as a core, Robyn was created. Robyn is one of the fastest Python web frameworks in the current Python web ecosystem. With a runtime written in Rust, Robyn achieves near-native rust performance while still having the ease of writing Python code. This talk will focus on the increased involvement of Rust in the Python ecosystem. It will also demonstrate why Robyn was created, the technical decisions behind Robyn, the increased performance by using the Rust runtime, how to use Robyn to develop web apps, and most importantly, how the community is helping Robyn grow! I will briefly demonstrate my experience and challenges of building a community around the project and how it allowed Robyn to ensure a smooth sail even in turbulent situations. I shall also share my future plans for Robyn. PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/GJDJEX/ Saphire C - Web Dev Sanskar Jethi PUBLISH QNRE9W@@pretalx.com -QNRE9W Unleashing the Power of Domain Driven Design and AWS with Python microservices en en 20230519T150000 20230519T152500 002500

Unleashing the Power of Domain Driven Design and AWS with Python microservices

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/QNRE9W/ Saphire C - Web Dev Justinas Kuizinas PUBLISH QTYMV3@@pretalx.com -QTYMV3 The Ultimate Matchmaker: Building Recommender Systems with TensorFlow en en 20230519T110000 20230519T115500 005500

The Ultimate Matchmaker: Building Recommender Systems with TensorFlow

In today's digital world, personalized recommendations have become an essential part of user engagement and retention. With the abundance of data available, building effective recommendation systems can seem daunting. In this workshop, we will take a deep dive into the world of TensorFlow Recommender Systems and explore the techniques and tools necessary to build a high-performing recommendation engine. We will start by understanding the fundamentals of recommender systems and how TensorFlow can be used to build them. We will then explore the different types of recommenders, including content-based, collaborative filtering, and hybrid models. We will also delve into the various evaluation metrics used to measure the effectiveness of recommender systems. In the second half of the workshop, we will get hands-on experience with TensorFlow Recommender Systems. We will work through a real-world use case and learn how to prepare the data, build and train the model, and make recommendations. By the end of the workshop, attendees will have a solid understanding of the key concepts and tools required to build powerful recommender systems using TensorFlow. They will have the opportunity to apply what they have learned and create their own personalized recommendations. Whether you're a data scientist, engineer, or product manager, this workshop is the perfect opportunity to dive deeper into the world of TensorFlow Recommender Systems and take your skills to the next level. PUBLIC CONFIRMED Workshop https://pretalx.com/pycon-lt-2023/talk/QTYMV3/ Coral A - Workshop Ashmi Banerjee PUBLISH ZKFXNW@@pretalx.com -ZKFXNW PyCharm, let's discuss your problems en en 20230519T120000 20230519T122500 002500

PyCharm, let's discuss your problems

PUBLIC CONFIRMED Workshop https://pretalx.com/pycon-lt-2023/talk/ZKFXNW/ Coral A - Workshop Alexander Podkhalyuzin PUBLISH NBRSE9@@pretalx.com -NBRSE9 Unlocking the Power of PySpark: A Comprehensive Workshop en en 20230519T140000 20230519T153000 013000

Unlocking the Power of PySpark: A Comprehensive Workshop

Are you looking for a powerful tool to tackle your big data problems? PySpark may be just what you need. Join us for a comprehensive workshop on PySpark, where we'll cover everything from the basics of parallel processing and lazy evaluation to deploying production-level solutions on a large scale. In this workshop, we'll start by visiting the key concepts of PySpark and exploring how it can help us solve business problems with potentially very large amounts of data. We'll then dive into working with DataFrames as a convenient layer of RDDs and utilizing an optimizer to get the most out of our data. To help you put your new knowledge into practice, we'll simulate a real-world business problem and walk you through the entire process of data preparation, model training with MLLib, and performing inference on preprocessed test data. We'll also add a business logic layer to our solution for further customization. Throughout the conference, we'll utilize the Spark UI to monitor and optimize our processes. We'll provide you with code that can be easily adapted to run on various platforms, including a cluster in AWS Glue and localhost. In addition, we'll cover optional content on lessons learned from large-scale production systems based on PySpark. We'll share insights on how to optimize performance and scale your solution to handle big data with ease. Whether you're just starting out with PySpark or looking to take your skills to the next level, this workshop is designed for you. Join us to discover how to harness the power of PySpark for big data and take your business to the next level. PUBLIC CONFIRMED Workshop https://pretalx.com/pycon-lt-2023/talk/NBRSE9/ Coral A - Workshop Carsten Frommhold PUBLISH QUFPJE@@pretalx.com -QUFPJE Leader talks en en 20230519T120000 20230519T122500 002500

Leader talks

PUBLIC CONFIRMED Talk https://pretalx.com/pycon-lt-2023/talk/QUFPJE/ Coral B - Workshop Travis Oliphant PUBLISH RBTWQC@@pretalx.com -RBTWQC Similarity search in practice or how AI can help in everyday’s life en en 20230519T140000 20230519T145500 005500

Similarity search in practice or how AI can help in everyday’s life

We dive into usage of Pytorch library and existing pre-trained models, to construct Image/Text/Audio search from scratch, using existing AI pipelines. The investigation of paralelization of computations using numba (cuda) library will expand the speeup cases. PUBLIC CONFIRMED Workshop https://pretalx.com/pycon-lt-2023/talk/RBTWQC/ Coral B - Workshop Linas Petkevičius