Feb 15, 2023
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By Alexandra Quinn
Seagate is the world’s leading data storage solution. Together with Iguazio, Seagate is able to manage data engineering at scale while harnessing petabytes of data, efficiently utilize resources, bridge the gap between data engineering and data science and create one production-ready environment with enterprise capabilities. In this new webinar, Vamsi Paladugu, Sr.
Jan 23, 2023
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By Asaf Somekh
8 years ago, when I founded Iguazio together with my co-founders Yaron Haviv, Yaron Segev & Orit Nissan-Messing, I never thought I would be making this announcement on our company blog: McKinsey acquired Iguazio! When we first embarked on this journey, we realized that while AI has the ability to transform any industry - from banking to retail to manufacturing - in reality most data science projects fail.
Dec 21, 2022
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By Nick Schenone and Xingsheng Qian and Brennan Smith
Enterprises who are actively increasing their AI maturity in a bid to achieve business transformations often find that with increased maturity comes increased complexity. For use cases that require very large datasets, the tech stacks required to meet business needs quickly become unwieldy.
Dec 14, 2022
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By Yaron Haviv
In 2022, AI and ML came into the mainstream consciousness, with generative AI applications like Dall-E and GPT AI becoming massively popular among the general public, and ethical questions of AI usage stirring up impassioned public debate. No longer a side project for forward-thinking businesses or CEOs that find it intriguing, AI and ML are now moving towards the center of the business.
Dec 11, 2022
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By Sahar Dolev-Blitental
The IDC MarketScape: Worldwide Machine Learning Operations Platforms 2022 Vendor Assessment is an annual study that evaluates technology vendors based on a comprehensive framework. It provides an in-depth quantitative and qualitative assessment of MLOps solution vendors in a long-form research report, to help buyers make important technology decisions that will create long term business success.
Dec 7, 2022
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By Sahar Dolev-Blitental
The GigaOm Radar reports support leaders looking to evaluate technologies with an eye towards the future. In this year's Radar for MLOps report, GigaOm gave Iguazio top scores on multiple evaluation metrics, including Advanced Monitoring, Autoscaling & Retraining, CI/CD, and Deployment. Iguazio was therefore named a leader and also classified as an Outperformer for its rapid pace of innovation.
Nov 29, 2022
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By Alexandra Quinn
The manufacturing industry can benefit from AI, data and machine learning to advance manufacturing quality and productivity, minimize waste and reduce costs. With ML, manufacturers can modernize their businesses through use cases like forecasting demand, optimizing scheduling, preventing malfunctioning and managing quality. These all significantly contribute to bottom line improvement.
Nov 17, 2022
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By Alexandra Quinn
Hugging Face is a popular model repository that provides simplified tools for building, training and deploying ML models. The growing adoption of Hugging Face usage among data professionals, alongside the increasing global need to become more efficient and sustainable when developing and deploying ML models, make Hugging Face an important technology and platform to learn and master.
Oct 11, 2022
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By Xingsheng Qian
With the Apache Spark 3.1 release in early 2021, the Spark on Kubernetes project has been production-ready for a few years. Spark on Kubernetes has become the new standard for deploying Spark. In the Iguazio MLOps platform, we built the Spark Operator into the platform to make the deployment of Spark Operator much simpler.
Sep 20, 2022
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By Adi Hirschtein
When operationalizing machine and deep learning, a production-first approach is essential for moving from research and development to scalable production pipelines in a much faster and more effective manner. Without the need to refactor code, add glue logic and spend significant efforts on data and ML engineering, more models will make it to production and with less issues like drift.
Mar 2, 2023
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By Iguazio
Hear from Iguazio's Director of Product Management, Gilad Shaham, as he explains the proven production-first approach for scaling your ML operations.
Nov 23, 2022
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By Iguazio
In this session, Jiri shares enterprise secrets to establishing efficient systems for ML/AI and how his team: Watch Jiri and Yaron's fascinating deep dive into HCI’s journey to MLOps efficiency.
Oct 26, 2022
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By Iguazio
Watch Julien Simon (Hugging Face), Noah Gift (MLOps Expert) and Aaron Haviv (Iguazio) discuss how you can deploy models into real business environments, serve them continuously at scale, manage their lifecycle in production, and much more in this on-demand webinar!
Oct 6, 2022
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By Iguazio
A demo showing how to use our feature store in conjunction with Snowflake. Focusing on.
Sep 12, 2022
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By Iguazio
Watch this video with Yaron, CTO and Co-Founder of Iguazio as he dives into different features and ways to use Iguazio's open source tool, MLRun.
Aug 16, 2022
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By Iguazio
Take a look at this product overview in-depth tutorial of the Iguazio MLOps Platform.
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The Iguazio Data Science Platform automates MLOps with end-to-end machine learning pipelines, transforming AI projects into real-world business outcomes. It accelerates the development, deployment and management of AI applications at scale, enabling data scientists to focus on delivering better, more accurate and more powerful solutions instead of spending their time on infrastructure.
The platform is open and deployable anywhere - multi-cloud, on prem or edge. Iguazio powers real-time data science applications for financial services, gaming, ad-tech, manufacturing, smart mobility and telecoms.
Dive Into the Machine Learning Pipeline:
- Collect and Enrich Data from Any Source: Ingest in real-time multi-model data at scale, including event-driven streaming, time series, NoSQL, SQL and files.
- Prepare Online and Offline Data at Scale: Explore and manipulate online and offline data at scale, powered by Iguazio's real-time data layer and using your favorite data science and analytics frameworks, already pre-installed in the platform.
- Accelerate and Automate Model Training: Continuously train models in a production-like environment, dynamically scaling GPUs and managed machine learning frameworks.
- Deploy in Seconds: Deploy models and APIs from a Jupyter notebook or IDE to production in just a few clicks and continuously monitor model performance.
Bring Your Data Science to Life.