AutoML in Fabric Data Science - automated model training and optimization (do more with less work!)

🔍 Microsoft Fabric offers Data Science experiences to empower users to complete end-to-end data science workflows for the purpose of data enrichment and business insights. You can complete a wide range of activities across the entire data science process, all the way from data exploration, preparation and cleansing to experimentation, modeling, model scoring and serving predictive insights to BI reports.

AutoML (Automated Machine Learning) is a collection of methods and tools that automate machine learning model training and optimization with little human involvement. The aim of AutoML is to simplify and speed up the process of choosing the best machine learning model and hyperparameters for a given dataset, which usually demands much skill and computing power.

In Fabric, data scientists can use flaml.AutoML to automate their machine learning tasks.

AutoML can help ML professionals and developers from different sectors to:

1. Build ML solutions with minimal coding

2. Reduce time and cost

3. Apply data science best practices

4. Solve problems quickly and efficiently

Read more: https://learn.microsoft.com/en-us/fab...



🎙 Meet the Speakers:

👤 Guest from Microsoft Fabric Product Group: Misha Desai, Senior Program Manager at Microsoft



Misha is a Senior Product Manager based in Seattle, WA, specializing in model tracking, training, and governance within the Fabric Data Science team.

Linkedin: www.linkedin.com/in/misha-desai-6034a362



👤 Host: Estera Kot Estera Kot, PhD, Principal Product Manager at Microsoft.

LinkedIn:   / esterakot  
Twitter:   / estera_kot  

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