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Machine Learning

Gen AI for Marketing - From Hype to Implementation - MLOps Live #32 with McKinsey and Iguazio

In this MLOps Live session we were joined by Eli Stein, Partner and Modern Marketing Capabilities Leader at McKinsey, to delve into how data scientists can leverage generative AI to support the company’s marketing strategy. We showcased a live demo of a customer-facing AI agent developed for a jewelry retailer, which can be used as a marketing tool to offer personalized product recommendations and purchasing information and support. Following the demo, we held an interactive discussion and Q&A session. Enjoy!

Qlik AutoML Series - Predict, Explain, Act - Explainer

Predict, Explain, Act with Qlik AutoML, a powerful tool that brings automated machine learning to the hands of business users and data analysts. In this all new series, revist and learn how Qlik AutoML allows you to build predictive models without needing deep technical expertise in data science. Follow along in the next few videos linked in the description as Mike Tarallo walks you through the key features, from experiment to deployment, and see how Explain-ability is defined and used to gain insights that drive decision-making. Perfect for those looking to enhance their analytics with AI-powered predictions!

Empowering Analytics Teams: Qlik AutoML's Next Evolution

In today's data-driven business landscape, the ability to predict trends, explain drivers, and act on insights is no longer a luxury—it's a necessity. Yet for many organizations, the path from data to predictive intelligence remains challenging. Data science resources are scarce, and traditional tools often require specialized expertise that most analytics teams lack. At Qlik, we believe that the power of predictive analytics should be accessible to all.

Launch Jobs & Setup Online Development Environments Directly from CLI

When it comes to managing AI projects, the Command Line Interface (CLI) can be a powerful tool. With ClearML, the CLI becomes an essential resource for creating job templates, launching remote for JupyterLab, VS Code, or SSH development environments, and executing code on a remote machine that can better meet resource needs. Specifically designed for AI workloads, ClearML’s CLI offers seamless control and efficiency, empowering users to maximize their AI efforts.

Why Multi-tenancy is Critical for Optimizing Compute Utilization of Large Organizations

As compute gets increasingly powerful, the fact of the matter is: most AI workloads do not require the entire capacity of a single GPU. Computing power required across the model development lifecycle looks like a normal bell curve – with some compute required for data processing and ingestion, maximum firepower for model training and fine-tuning, and stepped-down requirements for ongoing inference.

ClearML Announces AI Infrastructure Control Plane

We are excited to announce the launch of our AI Infrastructure Control Plane, designed as a universal operating system for AI infrastructure. With this launch, we make it easier for IT teams and DevOps to gain ultimate control over their AI Infrastructure, manage complex environments, maximize compute utilization, and deliver an optimized self-serve experience for their AI Builders.