Additional Authors: Amir Jafari, Shreyas Radhakrishna, Nellie Gustafsson We’re excited to unveil significant enhancements to the AI Skill in Fabric! These updates make it easier than ever to build a powerful generative AI data agent, helping you to unlock deeper insights and streamline decision-making. With improved flexibility, intelligence, and user-friendliness, the updated AI Skill is … Continue reading “New improvements coming to the AI Skill”
In today’s data-driven world, quickly developing and deploying machine learning (ML) models is essential. Automated Machine Learning (AutoML) streamlines this process, enabling analysts, data scientists, and domain experts to leverage ML without extensive coding. Now, with the launch of low code AutoML in Fabric Data Science, ML is more accessible than ever, regardless of technical … Continue reading “Announcing low code Automated ML (AutoML) in Fabric Data Science”
At Fabric, we’re passionate about contributing to the open-source community, particularly in areas that advance the usability and scalability of machine learning tools. One of our recent endeavors has been making substantial contributions back to the FLAML (Fast and Lightweight AutoML) project, a robust library designed to automate the tedious and complex process of machine … Continue reading “Enhancing Open Source: Fabric’s Contributions to FLAML for Scalable AutoML”
At the recent Fabric Conference, we announced that both code-first automated machine learning (AutoML) and hyperparameter tuning are now in Public Preview, a key step in making machine learning more complete and widely accessible in the Fabric Data Science. Our system seamlessly integrates the open-source Fast Library for Automated Machine Learning & Tuning (FLAML), offering … Continue reading “Introducing Code-First AutoML and Hyperparameter Tuning: Now in Public Preview for Fabric Data Science”
