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Mit AWS Peronalise bekommen Sie das Know-how der AWS Data Scientists in einer Box."},{"type":"p","text":"Mehr ..."},{"type":"h3","text":"AWS Forecast"},{"type":"p","text":"Mit AWS Forecast steht Ihnen ein Deep Learning-Modell zur Verfügung, das für Zeitreihenprobleme optimiert wurde."},{"type":"p","text":"Mehr ..."},{"type":"h3","text":"AWS Greengrass"},{"type":"p","text":"Greengrass ist eigentlich eine IoT-Lösung, bringt aber auch das nötige Handwerkzeug mit, um Machine Learning-Modelle auf dem Edge Device zu deployen."},{"type":"p","text":"Mehr ..."},{"type":"h2","text":"AWS Sagemaker"},{"type":"p","text":"Sagemaker Notebooks bieten die Entwicklungsumgebung – quasi die Werkbank der Data Scientisten und Engineers! Mit Verbindung zu AWS EMR können große Datenmengen für die Verarbeitung herangezogen werden. Ground Truth erlaubt die Erzeugung von Trainingsdatensätzen, entweder in der eigenen Firma oder mithilfe von Click-Workern."},{"type":"p","text":"Das Training von Machine Learning-Modellen erfolgt auf  speziellen Trainignsinstanzen, die auf das individuelle Problem skalliert werden. Die Bestimmung von Modellparametern (Hyperparametertuning) kann ebenfalls automatisiert werden - falls notwendig. Das trainierte Modell kann direkt auf spezifische \"Inference\"-Instanzen deployed werden, sodass die AI in den Business-Prozess integriert wird. Was passiert wenn das Modell nicht mehr zur Situation passt? Dann können DevOps ohne Probleme die Modelle neu trainieren, ohne das Zutun eines Data Scientists."},{"type":"p","text":" "},{"type":"h3","text":"Projekte bei unseren Kunden mit AWS Sagemaker "},{"type":"h4","text":"Object Detection mit Lasersensoren"},{"type":"h4","text":"Recommendation in der Vertriebssteuerung"},{"type":"h4","text":"Predictive Quality Assurance bei Reibeprozessen"},{"type":"h4","text":"Vertriebsplanung unterstützt durch künstliche Intelligenz"},{"type":"h2","text":"AWS Personalise"},{"type":"p","text":"Produktempfehlungen wie Amazon machen? Mit AWS Personalise bekommen Sie das Know-how der AWS Data Scientists in einer Box – transparent durch Metriken und skalierbar durch die nötige Infrastruktur. "},{"type":"h3","text":"Projekte bei unseren Kunden mit AWS EMR "},{"type":"h4","text":"Empfehlungen (Recommendations) in der Vertriebssteuerung"},{"type":"h4","text":"Automatische Content-Aussteuerung in Media-Applikationen"},{"type":"h4","text":"Empfehlungen in Webshops in der B2C-Produktvermarktung"},{"type":"h2","text":"AWS Forecast"},{"type":"p","text":"Zeitreihenanalyse und Forecasts gelten als althergebrachte und oft auch eingestaubte Methoden. Leider sind sie aus der Ökonometrie nicht ganz vollständig wegzudenken und komplexe Ansätze auch nur sehr schwer umzusetzen. Mit AWS Forecast existiert ein Tool, welches unfassbar viele Möglichkeiten bietet: Ein Deep Learning-Modell, das ganz spezifisch auf Zeitreihenprobleme optimiert wurde. Fehlende Datenpunkte, Ausreißer, zusätzliche Einflussfaktoren – kein Problem. Ohne großes Investment zeigen wir Ihnen die Möglichkeiten und überzeugen Sie von der Performance. Wenn die Ergebnisse stimmen, können die Modelle einfach und skalierbar deployed werden. "},{"type":"p","text":" "},{"type":"h2","text":"AWS Greengrass"},{"type":"p","text":"Nicht ganz richtig einsortiert im Bereich Machine Learning, aber unverzichtbar, wenn die Machine Learning-Modelle direkt am Ort des Geschehens notwendig sind. Greengrass ist eigentlich die IoT-Lösung von AWS, bringt aber auch das nötige Handwerkszeug mit, um Machine Learning-Modelle auf einem Edge Device zu deployen."},{"type":"p","text":" "},{"type":"h2","text":"Workshop-Angebote"},{"type":"p","text":"Wir bieten unseren Kunden und Interessenten eine Reihe von hochwertigen Workshops und Trainingsprogrammen an. 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Nehmen Sie Kontakt mit uns auf!"},{"type":"p","text":"Five1 GmbH - Member of the BTC Group"},{"type":"p","text":"Otto-Hahn-Straße 1c 69190 Walldorf"},{"type":"p","text":"Kontakt"},{"type":"p","text":"info@five1.de (+49) 6227 / 65318-70"},{"type":"p","text":"Folge uns bei"},{"type":"p","text":"Menü"},{"type":"p","text":"ImpressumDatenschutz"}],"loadingTime":7.656641483306885,"lastModifiedAt":"2023-03-14T00:00:00.000Z","metaData":{"title":"Machine Learning","description":"Machine Learning realisieren mit AWS Sagemaker, AWS Personalise, AWS Forecast für Deep Learning-Modelle oder AWS Greengrass als IoT-Lösung.","tags":["Machine Learning","Maschinelles Lernen","AWS Sagemaker","AWS Personalise","\nAWS Forecast","AWS Greengrass","AWS Forecast für Deep Learning","IoT-Lösung"],"image":{"internalName":"Machine_Learning.png#keepProtocol","name":"Machine_Learning.png#keepProtocol","url":"https://www.five1.de/hubfs/Machine_Learning.png#keepProtocol"}},"classification":{"label":"PRODUCT","isVerified":true}},"score":2258.6191,"company":{"_id":"649c35b52f66472b9af3b26c","name":"FIVE1 GmbH & Co.KG","description":"Five1 ist wie Du: Wir sind die Heimat von Individualisten, IT-Spezialisten, Technik-Nerds und Datenprofis. 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Artists and studios can achieve results they couldn’t before and get to the final creative faster by removing drudge work. Through ongoing research and product development, our aim is to provide the framework by which artists can gain creative freedom and control to apply the technology to create beautiful images. Foundry’s compositing tool Nuke has a full suite of tools to make machine learning accessible, empowering artist and algorithm to work in harmony."},{"type":"h3","text":"Nuke’s CopyCat: making machine learning accessible"},{"type":"p","text":"We've implemented machine learning in a way that is aligned with the ethos of Nuke—that artists should have full technical and creative control over their shots. This is why we created CopyCat, an ML tool released in Nuke 13.0 that solves impossible problems while being entirely controlled by the artist. Tasks like deblur, rotoscoping, and beauty work that previously took days to work on can now be resolved in a matter of hours."},{"type":"p","text":"Show me more"},{"type":"h3","text":"Machine learning for the masses: Inference & Nuke 13.1"},{"type":"p","text":"Nuke’s Inference node is used to apply CopyCat models to images in Nuke. Nuke 13.1 saw the functionality of this node extended via third party PyTorch model support, allowing users to bring their own machine learning models into Nuke, and run them performantly and reliably. This opens up Nuke to a broad range of community generated ML models."},{"type":"p","text":"More on ML in Nuke 13.1"},{"type":"h3","text":"Tackle industry challenges"},{"type":"p","text":"Accelerate your creativity Smash deadlines and meet demands with a comprehensive ML toolkit at your fingertips in Nuke’s industry-leading architecture, supporting rapid creative workflows—without sacrificing quality. Scale projects and processes Work easily at scale with CopyCat, allowing users to train neural networks to complete a whole range of tasks using only a small number of reference frames. Automate the mundane Nuke’s Upscale and Deblur nodes use a pre-trained machine learning network to enable artists to resize footage by x2 and remove motion blur from footage quickly and easily, so you can crack on with creative work faster. Reduce manual tasks Automate the more mundane tasks and save huge amounts of time, especially when facing tight deadlines. With this extra time, you can spend more time focusing on the creative side of things rather than boring manual tasks."},{"type":"h4","text":"Accelerate your creativity"},{"type":"p","text":"Smash deadlines and meet demands with a comprehensive ML toolkit at your fingertips in Nuke’s industry-leading architecture, supporting rapid creative workflows—without sacrificing quality."},{"type":"h4","text":"Scale projects and processes"},{"type":"p","text":"Work easily at scale with CopyCat, allowing users to train neural networks to complete a whole range of tasks using only a small number of reference frames."},{"type":"h4","text":"Automate the mundane"},{"type":"p","text":"Nuke’s Upscale and Deblur nodes use a pre-trained machine learning network to enable artists to resize footage by x2 and remove motion blur from footage quickly and easily, so you can crack on with creative work faster."},{"type":"h4","text":"Reduce manual tasks"},{"type":"p","text":"Automate the more mundane tasks and save huge amounts of time, especially when facing tight deadlines. 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With multi-shot management, editorial and compositing in a single application, you can experience greater creative control, work seamlessly from start to delivery, and experiment with AI and automation workflows to get to that final pixel-perfect image faster. Explore Nuke Studio"},{"type":"h4","text":"Advanced, industry-standard compositing"},{"type":"h4","text":"Multi-shot management, editorial and compositing"},{"type":"h3","text":"Framestore accelerates their creative process using Nuke’s CopyCat"},{"type":"p","text":"We caught up with Framestore to find about the creative process behind anti-knife campaign Long Live The Prince, and how machine learning technology in the form of Nuke’s CopyCat node was deftly used to benefit the production."},{"type":"p","text":"Read more here"},{"type":"h3","text":"Learn more"},{"type":"p","text":"Introduction to Machine Learning in Nuke Learn how the visual effects industry is impacted by machine learning, and how you can introduce it to your compositing workflows in Nuke. Show me more Get started with CopyCat Discover how to train the neural network inside CopyCat to replicate sequence-specific effects, such as beauty repairs, shot clean-up, garbage matting, or deblurring. 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Show me more Get started with CopyCat Discover how to train the neural network inside CopyCat to replicate sequence-specific effects, such as beauty repairs, shot clean-up, garbage matting, or deblurring. Watch now Discover near real-time Go behind-the-scenes of Comandante and discover how the novel technique near real-time was developed to meet the production constraints of the project. Take me there Using AI to Speed Up Your VFX Shot Prep Discover how to use Nuke’s CopyCat node to perform preliminary work on a VFX shot and let AI do the heavy lifting—so you don’t have to. 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Contact Us"},{"type":"p","text":"Discuss, inquire, and discover with other practitioners."},{"type":"h1","text":"Machine Learning"},{"type":"h2","text":"Optimize Machine Learning Models for Production"},{"type":"p","text":"Putting models into production is one of the greatest challenges for data science teams, and hyperparameter tuning is one of the main barriers to that process. Our optimization solution accelerates the model development process for machine learning practitioners and enables experiment reproducibility during that process. Even after being put in production, models can experience drift as data changes, and SigOpt allows data science teams to build a robust process around continuously optimizing models."},{"type":"h2","text":"Seamless Integration into Your Model"},{"type":"p","text":"Practitioners integrate SigOpt into their model either via one of our supported client libraries or directly through the REST API. 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