ODSC Europe | June 15 - 16, 2022 | In-person and Virtual

Vector Search

Learn the latest models, advancements, and trends from the top practitioners behind one of the field's hottest topics
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    FOCUS AREA OVERVIEW

    Complex data such as text, documents, video, and images,, abound in many organizations but can be difficult to search, and in turn, utilize in products or services. Machine Learning can provide a far more helpful representation of complex data by transforming it into vector embeddings that describe complex data objects as numeric values at very high dimensions. These vector embeddings can be indexed and stored in vector databases for quick retrieval and similarity search, Vector databases are very good at vector search (similarity search). Vector search enables users to describe what they want to find without having to know which keywords or metadata classifications are attributed to the stored objects. Use cases for vector search include semantic search, recommendation systems, ranking, and similarity search for text, audio, images, video, and other types of unstructured data.

    TOPICS YOU'LL LEARN


    Vector Search

    Vector Embeddings

    Recommendation Systems

    Question Answering

    Vector Databases

    Semantic Search

    Data Classification

    Multimodal Search

    Confirmed Speakers


    Confirmed Talks


    An Introduction to Vector Databases and Vector Search

    In machine learning – like recommendation tools or data classification – data is often represented as high-dimensional vectors. These vectors are stored in so-called vector databases. Vector databases are the backbone of ML deployments in industry, they are designed and optimized to run search, ranking and recommendation algorithms.
    If you are a data scientist or a data/software engineer join Laura to learn how to run your favorite ML models with a vector database like Weaviate. But also to learn about other features like semantic search, question answering, data classification, named entity recognition, and multimodal search, that you should expect from a Vector Database.
    Finally, Vector search will be illustrated with live demos of a real use case! After this session, you will know when and how to use Vector Search with various ML models.

    Semantic Search in NLP – How to Build Question Answering with Haystack

    With the development of Transformer-based language models, NLP has had a leap in research and techniques in the last few years. These language models enable different tasks such as Question Answering, summarisation, translation, retrieval and so on. These, combined with vector optimized databases and the development of Open Source frameworks such as Haystack have made it possible for us to create NLP powered applications to a quality that was previously not possible. This talk will cover an intro to NLP and Question Answering, followed by an example on how to build a Question Answering pipeline with Haystack.

    Vector Search for Data Scientists

    Finding metrics that describe performance can unlock valuable insights in the field of Data Science.  It can be helpful to visualize the distribution of these metrics and to understand how segments of metrics vary with each other. It is needed here to define categories such as age or gender that can divide the data, which is a limitation of segmenting analytics. Vector Search uses semantics to analyze data, and does not have the limitation of requiring  symbolic tags. In this talk, you will learn how to use Vector Search as a Data Scientist. By means of real Youtube and Twitter data, you’ll see how easy it is to utilize this yourself with the Vector Search engine Weaviate

    Why Attend?


    Immerse yourself in talks, tutorials, and workshops on Machine Learning and Deep Learning tools, topics, models and advanced trends

    Expand your network and connect with like-minded attendees to discover how Machine Learning and Deep Learning knowledge can transform not only your data models but also your business and career

    Meet and connect with the core contributors and top practitioners in the expanding and exciting fields of Machine Learning and Deep Learning

    Learn how the rapid rise of intelligent machines is revolutionizing how we make sense of data in the real world and its coming impact on the domains of business, society, healthcare, finance, manufacturing, and more

    ODSC EUROPE Hybrid Conference 2022 | June 15 - 16th

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