Dr. Qiyang Duan
Alibaba Big Data and Machine Learning Technology
#1about 4 minutes
How e-commerce scale drives Alibaba's big data technology
Alibaba's big data platform evolved to handle massive transaction volumes from events like the Double 11 festival, processing petabytes of data daily.
#2about 4 minutes
Exploring Alibaba's big data and AI product portfolio
The platform is structured around a typical data flow, including tools for data ingestion, storage, processing, visualization, and a dedicated AI platform called PAI.
#3about 4 minutes
Comparing core data processing engines on Alibaba Cloud
A look at key processing tools including MaxCompute for massive-scale SQL, E-MapReduce for Hadoop migrations, and Flink for real-time stream processing.
#4about 5 minutes
Using DataWorks as a unified IDE for big data
DataWorks provides a single environment for data development and operations, integrating various engines like MaxCompute and Hadoop and including data governance tools.
#5about 7 minutes
Developing models with the Platform for AI (PAI)
The PAI platform supports both visual drag-and-drop model building with PAI Studio and code-based development using the Data Science Workshop (DSW) with JupyterLab.
#6about 2 minutes
Announcing the Alibaba Cloud AI Champion 2020 competition
An overview of the AI Champion 2020 competition, which offers cash prizes and cloud credits for innovative projects built on the PAI platform.
#7about 5 minutes
Live demo of data analysis with DataWorks
A walkthrough of the DataWorks interface, demonstrating how to write and execute SQL queries, visualize results, and manage data integration jobs.
#8about 8 minutes
Live demo of building models on the PAI platform
A demonstration of building a recommendation model using the drag-and-drop PAI Studio and running a deep learning example in the PAI-DSW JupyterLab environment.
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Exploring the serverless ecosystem on Alibaba Cloud
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Showcasing real-time AI application examples
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Building a data-driven culture with ALDI Data & Analytics
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Global expansion and AI-powered learning platforms
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The production architecture and technology stack for AML AI
Detecting Money Laundering with AI
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Q&A on AI adoption, tools, and challenges
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Q&A on parallel computing, data versioning, and security
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