Presented By
O’REILLY + INTEL AI

English中文
PUT AI TO WORK
June 18-21, 2019
Beijing, CN

通过自动化机器学习民主化和加速AI落地 (Democratizing and Accelerating AI through Automated Machine Learning)

此演讲使用中文 (This will be presented in Chinese)

Sujatha Sagiraju (Microsoft), Henry Zeng (Microsoft)
13:3017:00 Wednesday, June 19, 2019

必要预备知识 (Prerequisite Knowledge)

- Understand the basic concepts and process of machine learning and deep learning - Have experience of building machine learning models - Hands on with Python on Machine learning such as sklearn, TF and Keras

您将学到什么 (What you'll learn)

By attending the tutorial, the audience will: 1. Understand the process of ML flow, and the current pain points of feature engineering, algorithm selection and hyper parameter tuning 2. Get started quickly using Python with AutoML 3. How to use AutoML technology to automate the model training workflow based on sklearn and lightgbm for statistical learning 4. How to use AutoML technology to auto tune the hyper-parameters in deep learning model to reduce deep learning training pains, time and cost 5. Tips and best practices while conduct model training with AutoML 6. Review, deploy and consume the model created by AutoML

描述 (Description)

Automated ML is based on a breakthrough from our Microsoft Research division. The approach combines ideas from collaborative filtering and Bayesian optimization to search an enormous space of possible machine learning pipelines intelligently and efficiently. It’s essentially a recommender system for machine learning pipelines. Similar to how streaming services recommend movies for users, automated ML recommends machine learning pipelines for data sets.
 
Just as important, automated ML accomplishes all this without having to see the customer’s data, preserving privacy. Automated ML is designed to not look at the customer’s data. Customer data and execution of the machine learning pipeline both live in the customer’s cloud subscription (or their local machine), which they have complete control of. Only the results of each pipeline run are sent back to the automated ML service, which then makes an intelligent, probabilistic choice of which pipelines should be tried next.
 
Microsoft is committed to democratizing AI through our products. By making automated ML available through the Azure Machine Learning service, we’re empowering data scientists with a powerful productivity tool. We’re working on making automated ML accessible through PowerBI, so that business analysts and BI professionals can also take advantage of machine learning. And stay tuned as we continue to incorporate it into other product channels to bring the power of automated ML to everyone.
 
Focusing on the Data Science and Artificial intelligence track theme, this session will provide an overview of Automated machine learning, key customer use-cases, how it works and how you can get started. This workshop has been previously delivered to an audience of 200 attendees and can be delivered to over 300 attendees.

Photo of Sujatha Sagiraju

Sujatha Sagiraju

Microsoft

Sujatha Sagiraju is a Group Program Manager in the Azure Cloud & AI group. Her expertise is in building large scale distributed systems. Her latest mission is accelerating and democratizing Artificial Intelligence via Automated Machine Learning. She has been at Microsoft since 2001 in various roles including developer, program manager and capacity planner. Other interests – Sujatha is a diversity & inclusion champion at the Azure AI platform org and is passionate about recruiting, mentoring and growing diverse talent.

Photo of Henry Zeng

Henry Zeng

Microsoft

Henry Zeng is a principal program manager in the Cloud AI Group at Microsoft, where he works with engineering team, partners and customers to ensure the success of ML platform. He has been in AI and data area for more than 10 years from database, NoSQL, Hadoop ecosystem, machine learning to deep learning. Prior to this role, he was the lead AI solution architect in Microsoft China working with partners and customer to land AI solutions in manufactory, retail, education and public service etc with Microsoft AI offerings. Henry holds a MS in computer science from Wuhan University.

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