List of videos

Dinesh Subramani Solutions Architect @ AWS In this session, we showcase the power of machine learning in taking a large corpus of a foreign language text (we use the entire Wikipedia) and automatically learning word embeddings for that language. This is typically the first key step in building natural language processing (NLP) solutions, such as text classification or topic modelling. You see how easy it is to apply the BlazingText algorithm built into Amazon SageMaker in order to process the entire contents of Wikipedia in this language and visualize the results. You then can apply these learnings to any language of your choice. — 0:00 Intro 0:20 Talk — 🥇 Gold Sponsor AWS 🥈 Silver Sponsors ChaosNative Microsoft Restream SeMI Technologies Stream Native TypingDNA 🤝 Media Partners Bpb Infosec Conferences [ Inside Dev ] Manning O'Reilly Packt — Website 🚀🪐 https://www.conf42.com​ Reach Out 📧📭 mark@conf42.com Discord Server 🧑‍🤝‍🧑💬 https://discord.com/invite/dT6ZsFJ5ZM​ LinkedIn 👨‍💼💼 https://www.linkedin.com/company/4911...​ Twitter 🎵🐦https://twitter.com/conf42com​ Conf42Cast 🎧 http://www.conf42.com/podcast

Marianna Diachuk Data Scientist @ Restream It’s no secret that the deployment of the Machine Learning models conceptually is far from training those models and requires a different mindset. Some deal with it by having people dedicated to work on deployment since there’s actually a lot to do even when the model is still in the development phase and some just expect data scientists to do everything from modeling and analysis to deployment and monitoring. In this talk I’d like to share my experience with deployment starting from 2017 as well as the lessons I’ve learned. Wait for a couple of wild and sometimes embarrassing stories but at least (oops) I didn’t do it again. — 0:00 Intro 0:20 Talk — 🥇 Gold Sponsor AWS 🥈 Silver Sponsors ChaosNative Microsoft Restream SeMI Technologies Stream Native TypingDNA 🤝 Media Partners Bpb Infosec Conferences [ Inside Dev ] Manning O'Reilly Packt — Website 🚀🪐 https://www.conf42.com​ Reach Out 📧📭 mark@conf42.com Discord Server 🧑‍🤝‍🧑💬 https://discord.com/invite/dT6ZsFJ5ZM​ LinkedIn 👨‍💼💼 https://www.linkedin.com/company/4911...​ Twitter 🎵🐦https://twitter.com/conf42com​ Conf42Cast 🎧 http://www.conf42.com/podcast

Nicolas Metallo Senior Data Scientist @ AWS The University of Oxford houses 21 millions of objects in the collections of its Gardens, Libraries & Museums. Preserving these assets requires great care. In this talk, we will review how AWS helped them build a sector leading ML solution that increased access to its collections for students, researchers, and public visitors while saving its staff and volunteers a massive amount of work. This talk will show recent work related to the new AWS Case Study titled “University of Oxford introduces a sector leading Machine Learning prototype to augment Digitisation in Numismatics”. — 0:00 Intro 0:20 Talk — 🥇 Gold Sponsor AWS 🥈 Silver Sponsors ChaosNative Microsoft Restream SeMI Technologies Stream Native TypingDNA 🤝 Media Partners Bpb Infosec Conferences [ Inside Dev ] Manning O'Reilly Packt — Website 🚀🪐 https://www.conf42.com​ Reach Out 📧📭 mark@conf42.com Discord Server 🧑‍🤝‍🧑💬 https://discord.com/invite/dT6ZsFJ5ZM​ LinkedIn 👨‍💼💼 https://www.linkedin.com/company/4911...​ Twitter 🎵🐦https://twitter.com/conf42com​ Conf42Cast 🎧 http://www.conf42.com/podcast

Tim Spann Developer Advocate @ StreamNative A cloud data lake that is empty is not useful to anyone. How can you quickly, scalably and reliably fill your cloud data lake with diverse sources of data you already have and new ones you never imagined you needed. Utilizing open source tools from Apache, the FLaNK stack enables any data engineer, programmer or analyst to build reusable modules with low or no code. In this talk we will utilize Apache NiFi, Apache Pulsar, Apache Flink and MiNiFi agents to load CDC, Logs, REST, XML, Images, PDFs, Documents, Text, semistructured data, unstructured data, structured data and a hundred data sources you could never dream of streaming before. I will teach you how to fish in the deep end of the lake and return a data engineering hero. Let’s hope everyone is ready to go from 0 to Petabyte hero. — 0:00 Intro 0:20 Talk — 🥇 Gold Sponsor AWS 🥈 Silver Sponsors ChaosNative Microsoft Restream SeMI Technologies Stream Native TypingDNA 🤝 Media Partners Bpb Infosec Conferences [ Inside Dev ] Manning O'Reilly Packt — Website 🚀🪐 https://www.conf42.com​ Reach Out 📧📭 mark@conf42.com Discord Server 🧑‍🤝‍🧑💬 https://discord.com/invite/dT6ZsFJ5ZM​ LinkedIn 👨‍💼💼 https://www.linkedin.com/company/4911...​ Twitter 🎵🐦https://twitter.com/conf42com​ Conf42Cast 🎧 http://www.conf42.com/podcast

Joshua Arvin Lat CTO @ NuWorks Interactive Labs It is not an easy task to design and build systems in the cloud that involve Machine Learning and Data Science requirements. It also requires careful planning and execution to get different teams and professionals such as data scientists and members of MLOps teams to follow certain processes in order to have a sustainable and effective ML workflow. In this talk, I will share the different strategies and solutions on how to design, build, deploy, and maintain complex intelligent systems in AWS using Amazon SageMaker. Amazon SageMaker is a fully managed machine learning service that aims to help developers, data scientists, machine learning practitioners, and MLOps teams manage machine learning experiments and workflows. We will start by discussing some of the important concepts and patterns used in production environments and systems. As we discuss these concepts and patterns, we will provide a couple of practical solutions and examples on using the different features and capabilities of Amazon SageMaker to solve the different needs of data science and MLOps teams. — 0:00 Intro 0:20 Talk — 🥇 Gold Sponsor AWS 🥈 Silver Sponsors ChaosNative Microsoft Restream SeMI Technologies Stream Native TypingDNA 🤝 Media Partners Bpb Infosec Conferences [ Inside Dev ] Manning O'Reilly Packt — Website 🚀🪐 https://www.conf42.com​ Reach Out 📧📭 mark@conf42.com Discord Server 🧑‍🤝‍🧑💬 https://discord.com/invite/dT6ZsFJ5ZM​ LinkedIn 👨‍💼💼 https://www.linkedin.com/company/4911...​ Twitter 🎵🐦https://twitter.com/conf42com​ Conf42Cast 🎧 http://www.conf42.com/podcast

Conf42 Machine Learning 2022 kicks off right now! 🐕 Schedule, Lineup & RSVP: https://www.conf42.com/ml2022 🐈 Join Discord to interact: https://discord.gg/DnyHgrC7jC 0:00 intro, sponsors & partners Keynote 0:40 Jesus Saldana Gonzalez getting started 1:06 Felice Pescatore 2:15 Johannes Hotter 2:43 Vasco Veloso 3:39 Joshua Arvin Lat tools 4:12 Laura Ham 5:04 Julien Simon 5:35 Mohsin Khan 6:20 Andrew Knight lessons learned 6:48 Harika Chebrolu no intro - Aditi Ramaswamy & Anisha Biswaray 7:28 Wojtek Kuberski 8:12 Karan Singh 8:46 Thank you, Join our Discord to interact! https://discord.gg/DnyHgrC7jC

No one can deny that artificial intelligence is all the rage. After a cold winter, it is making a strong comeback with increasingly impressive advances. Maybe that's why people are starting to look with suspicion at this technology. But in this uncertain landscape, one thing is clear: machine learning won't put you out of a job, although you may never work the same way again. Other talks at this conference 🚀🪐 https://www.conf42.com/ml2022 — 0:00 Intro 0:22 Talk

Business Agility represents the ability of an organization to respond adequately to market, and at the same time dealing with internal flexibility for revising its organizational model, its own processes and specific skills, in order to make everything more efficient. Business Agility is a process of perpetual evolution that must focus on what is validated on the field in order to identify, from an experimental point of view, the best relative solution, that topically is in conflict with absolutisms. It is evident how the data collected within daily operations represent a real treasure, while emphasizing the importance of turning them into a valuable information that allows decisions to be made in a more targeted and prudent way. To achieve this, modern intelligence algorithms are increasingly used and become a precious ally to those who set themselves the ambitious challenge of implement an agile organization able to best support the vision of business agility. In the time available we will explore just how artificial intelligence can concretely support the organizational transformation process, also presenting the pilot project Arinn.ia, which is a Digital Agile Master that supports teams in their first experiments in agile scope. Other talks at this conference 🚀🪐 https://www.conf42.com/ml2022 — 0:00 Intro 0:22 Talk

In this talk, we will focus on the data perspective when building machine learning pipelines. Using two examples, I will show how greenfield and brownfield data labeling differ, what you should focus on in each, and how to best leverage new technologies, frameworks, and products to build high-performing models. The goal is to give you a better understanding of what data options you have for building machine learning pipelines (whether for classification or extraction). The ideas and concepts are based on research results from the Hasso Plattner Institute and three years of experience in consulting AI projects. Other talks at this conference 🚀🪐 https://www.conf42.com/ml2022 — 0:00 Intro 0:22 Talk