Simplifying Machine Learning with Automated ML

From the creator

Building accurate machine learning models requires a deep understanding of machine learning, as well as other data science and coding skills. Automated machine learning's purpose is to alleviate these requirements, automating the ML workflow of data cleansing, feature engineering, algorithm selection, hyperparameter tuning, and deployment. Enabling business domain experts to leverage ML in their day to day work using the web UI without writing a single line of code, as well as optimizing data scientists work by automating part of the technical work. Jump To: 00:55 - Start an Automated ML Experiment 03:07 - Analyze experiment outputs and deploy recommended model The AI Show's Favorite links: Don't miss new episodes, subscribe to the AI Show: https://aka.ms/aishowsubscribe Create a Free account (Azure): https://aka.ms/aishow-seth-azurefree Deep Learning vs. Machine Learning: https://aka.ms/AIShow/DLvML Get Started with Machine Learning: https://aka.ms/AIShow/StartML Follow: https://twitter.com/sethjuarez Follow: https://twitter.com/ch9 Follow: https://twitter.com/Azure Follow: https://twitter.com/msdev #ai #microsoftai #automatedml

Published 2019-11-04 · Watch on YouTube ↗
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