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LoginContact Pricing The Platform ML Platform Serverless Capabilities PriceHopsworks PlatformUse CaseBlogsEventsMLOps DictionaryExamplesNewsDocumentationUse CaseCustomersIntegrationsBlog Learn Docs MLOps Dictionary FAQ: EU AI Act Examples Resources Events News Community About Us ML PLATFORM WITH HIGHEST PERFORMANCE FEATURE STORE FOR BATCH AND REAL-TIME AI USE CASES. ANY DEPLOYMENT, ON PREMISES & CLOUD. USING THE PRINCIPLES OF MLOPS. Start for free Contact Use case for Paddy Power Use case for Arbetsformedlingen Use case for Paddy Power Use case for Arbetsformedlingen THE ML PLATFORM TO BUILD, MAINTAIN, AND MONITOR ML SYSTEMS BUILD MACHINE LEARNING SYSTEMS FOR REAL-TIME OR BATCH USE CASES. FEATURE STORE The most easy to use & capability rich feature store in the world. With built-for-purpose Online, Offline and Metadata Storages. Outperforming any platform. Feature Monitoring Computed Statistics Schema Versioning Lineage Data Versioning Spark Flink SQL Python Scheduler Backfill Orchestration MODEL REGISTRY Efficient and seemlessly integrated. Registry Accuracy Versioning MODEL SERVING Deploy a single model or thousands. Deployment Endpoint Testing Versioning CONTENT & INSIGHTS EXPLORE OUR VIDEOS, TUTORIALS, AND INDUSTRY LEADING CONTENT ON OUR BLOG The rapid development pace in AI is the cause for a lot of misconceptions surrounding ML and MLOps. In this post we debunk a few common myths about MLOps, LLMs and machine learning in production. At Hopsworks the F.A.I.R principles have been a cornerstone of our approach in designing a platform for managing machine learning data and infrastructure. We go through the most common errors messages in Pandas and offer solutions to these errors as well as provide efficiency tips for Pandas code. M MLOPS Dictionary MODEL SERVING P MLOPS Dictionary PLATFORM - KSERVE I MLOPS Dictionary INSTRUCTION DATASETS FOR FINE-TUNING LLMS T MLOPS Dictionary TWO-TOWER EMBEDDING MODEL EVENTS INCOMING EVENTS AND WEBINARS "Our journey with Hopsworks has been an amazing transformation that's really enabled us to be innovative and reach a point that we wouldn't have been able to reach otherwise.” RICHARD WOOLSTON DATA SCIENCE MANAGER - AFCU 1000S OF USERS JOIN THE EVER GROWING LIST OF LEADING COMPANIES USING HOPSWORKS. Use case for Paddy Power Use case for Arbetsformedlingen Use case for Paddy Power Use case for Paddy Power ROI WITH A FEATURE STORE Achieve an 80% reduction in cost over time starting from the second ML models are deployed in production. Read more GENERATING VALUE WITH AI MLOps with a feature store allows your organisation to put your data into production, faster. Read more CHOOSING A FEATURE STORE Accelerate your machine learning projects and unlock the full potential of your data with our feature store comparison guide. Read more HOPSWORKS CORE CAPABILITIES INCREASE TEAM PRODUCTIVITY AND DEPLOY YOUR MODELS FASTER. PYTHON Feature engineering at reasonable scale. Bring your own code with you, use any popular library and framework in Hopsworks. Learn more COLLABORATION Role-based access control, project-based multi-tenancy, custom metadata for governance. Learn more ENGINEERING Feature Engineering at scale, and with the freshest features. Batch or Streaming feature pipelines. Learn more BYO-CLOUD Bring Your Own Cloud, your infrastructure, on-premise or anywhere else; managed clusters on AWS, Azure, or GCP. Learn more PERFORMANCE Use Python, Spark or Flink with the highest performance pipelines for reading and writing features. Learn more SUPPORT Enterprise Support available 24/7 on your preferred communication channel. SLOs for your feature store. Join Slack CODES AND EXAMPLES TO GET YOU STARTED JUMP RIGHT IN WITH OUR LATEST CODE AND EXAMPLES. Batch On-demand Features Advanced Tutorial Real-Time TIMESERIES Timeseries price prediction based on previous prices and engineered features such as RSI, EMA, etc. Additional ressources: Go to the code Hopsworks Integration BYTEWAX Real-time feature computation using Bytewax. Additional ressources: Go to the code On-demand Features Hopsworks Integration REDSHIFT Create an External Feature Group using Redshift Storage Connector. Additional ressources: Go to the code Hopsworks API HOPSWORKS SECRETS API This example Hopsworks program shows the Python API for managing secrets in Hopsworks. Additional ressources: Go to the code Hopsworks Integration GREAT EXPECTATIONS WITH HOPSWORKS Introduction to Great Expectations concepts and classes which are relevant for integration with the Hopsworks MLOps platform. Additional ressources: Go to the code Hopsworks API HOPSWORKS DATASET API How to upload data to your cluster and download data from the cluster to your local environment. Additional ressources: Go to the code Go To Examples COMMUNITY Hopsworks @hopsworks Hopsworks goes to Gotland! 🏰 Our team recently embarked on an amazing team building trip to the beautiful island of Gotland. It was an incredible opportunity for us to bond, recharge, strengthen our collaborative spirit and embrace the sunny season! PyData @PyData With #PyDataLondon2023 around the corner, we want to thank @hopsworks for their platinum sponsorship! Sponsor support is vital in empowering the #datascience community and driving innovation. We're thrilled to have you 🐍✨ Join us this June 2-4! AI-Podden Technology/AI Podcast New Episode Alert 🎙 Happy Friday listeners, Tune in this week for remarkable insights and visionary perspectives that will leave you inspired and eager to embrace the fascinating world of AI. Together, we embark on a journey into the captivating realm of AI production, data pipelines, infrastructure, and the future of building AI systems in conversation with special guest; Jim Dowling, Founder and CEO of Hopsworks and Associate Professor in Computer Science at KTH Royal Institute of Technology. Jim shares remarkable insights on fast-tracking AI production and how organisations can quickly deploy AI algorithms into production. We also delved into the current state of AI, emerging trends, and many exciting possibilities on the horizon. 🎧 #AIProduction #DataInfrastructure #FutureofAI #AIInsights Jim Dowling @jim_dowling We started out writing a MLOps Glossary, but it became a dictionary. I hope it's useful for those who want to learn about MLOps and Feature Stores: Hopsworks @hopsworks We received an incredible gift!!! Thanks to the Semantic Layer Summit, @AtScale, for your note, and congratulations on an amazing Summit! Watch @jim_dowling's talk "Feature Store and the Semantic Layer" on demand! 📹 Paul Iusztin Senior Machine Learning Engineer Want to 𝗹𝗲𝗮𝗿𝗻 𝗠𝗟 & 𝗠𝗟𝗢𝗽𝘀 𝗶𝗻 𝗮 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝘄𝗮𝘆? After 6 months of work, I finally finished 𝘛𝘩𝘦 𝘍𝘶𝘭𝘭 𝘚𝘵𝘢𝘤𝘬 7-𝘚𝘵𝘦𝘱𝘴 𝘔𝘓𝘖𝘱𝘴 𝘍𝘳𝘢𝘮𝘦𝘸𝘰𝘳𝘬 Medium series. In 2.5 hours of reading & video materials, you will learn how to: - design a batch-serving architecture - use Hopsworks as a feature store - design a feature engineering pipeline that reads data from an API - build a training pipeline with hyper-parameter tunning - use W&B as an ML Platform to track your experiments, models, and metadata - implement a batch prediction pipeline - use Poetry to build your own Python packages - deploy your own private PyPi server - orchestrate everything with Airflow - use the predictions to code a web app using FastAPI and Streamlit - use Docker to containerize your code - use Great Expectations to ensure data validation and integrity - monitor the performance of the predictions over time - deploy everything to GCP - build a CI/CD pipeline using GitHub Actions - trade-offs & future improvements discussion #machinelearning #course #mlops Amaan Khan @Amaankhan4you hopsworks: Hopsworks - Data-Intensive AI platform with a Feature Store ⭐️ 812 #devopskhan #aws Hopsworks @hopsworks Introducing Hopsworks beers 2.0! 🍻☀️ As a team we are not just passionate about data and technology, we also happen to be a group of beer-loving individuals (hence the name). In fact, our love for beer runs so deep that we decided to take it a step further and brand our very own brews! Cheers! merve @mervenoyann Second workshop of the day that involves @huggingface Spaces & @Gradio, delivered by @jim_dowling 🤩 Check out his free course on serverless ML here 👉🏼 https://serverless-ml.org Pierre Brunelle @pjlbrunelle Making some new friends at @pydatanyc - something might be stacking up soon - @noteable_io x @hopsworks? Pau Labarta Bajo @paulabartabajo_ Wanna learn how to generate real-time features for a crypto trading bot? Here is an example with full source code ↓ Katonic.ai MLOps Platform 🚀 Unlock the full potential of your machine learning workflows with Hopsworks and Katonic! 🤝 Hopsworks offers a central repository for managing, sharing, and exploring features across projects. 📊 Katonic, a powerful MLOps platform, automates tasks from model development to deployment and monitoring, ensuring faster and more efficient ML workflows. 🚀 By integrating Hopsworks with Katonic, you can get consistent feature management, improved model quality, and accelerated model development and deployment, resulting in better collaboration and simplified governance. 📈 #MachineLearning #FeatureEngineering #MLOps #Hopsworks #Katonic #DataScience #AI Hopsworks @hopsworks We are here, and ready, at @PyDataNYC! Come and see hi 🔥 Serverless ML @ServerlessML Anytime! Watch #FSS2022! 🚀 We hosted an amazing panel moderated by @jim_dowling from @hopsworks. 'APIs for Feature Stores' discussed the historical evolution and the future of APIs for feature stores. PRODUCT The Feature StoreProduct CapabilitiesOpen SourceCustomersIntegrationsApp Status RESOURCES The MLOps DictionaryEU AI Act GuideExamplesUse-CasesBlogEventsDocumentationFeature Store ComparisonCommunityFAQ COMPANY About UsContact Us Slack Github Twitter Linkedin Youtube JOIN OUR MAILING LIST Subscribe to our newsletter and receive the latest product updates, upcoming events, and industry news. © Hopsworks 2024. All rights reserved. Various trademarks held by their respective owners. × NOTICE We and selected third parties use cookies or similar technologies for technical purposes and, with your consent, for other purposes as specified in the cookie policy. Use the “Accept” button to consent. Use the “Reject” button to continue without accepting. Press again to continue 0/2 Learn more and customize RejectAccept