Analytics Zoo provides a unified analytics plus AI platform that seamlessly unites Spark, TensorFlow, Keras, and BigDL programs into an integrated pipeline; the entire pipeline can then transparently scale out to a large Hadoop/Spark cluster for distributed training or inference.
Zhichao Li explains how you can build and productionize deep learning applications for big data (e.g., transfer learning-based image classification, sequence-to-sequence prediction for precipitation nowcasting, neural collaborative filtering for recommendations, unsupervised time-series anomaly detection, etc.) using Analytics Zoo with real-world use cases (such as JD.com, MLSListings, World Bank, UnionPay, midea/KUKA, etc.)
Analytics Zoo 提供了一个统一的“分析+人工智能”平台。它无缝地把Spark、TensorFlow、Keras和BigDL统一进一个集成的管道。整个管道可以透明地扩展到大型Hadoop和Spark集群上，以进行分布式的训练和推断。
在本次辅导课中我们将通过使用来自Analytics Zoo的真实案例（如京东、MLSListings、世界银行、银联、midea / KUKA等），展示如何面向大数据构建和生产化部署深度学习应用，例如，基于迁移学习的图像分类、使用序列到序列模型进行降水预报、基于神经协同过滤的推荐、无监督时间序列异常检测等。
Zhichao Li is a senior software engineer at Intel focused on distributed machine learning, especially large-scale analytical applications and infrastructure on Spark. He’s also an active contributor to Spark. Previously, Zhichao worked in Morgan Stanley’s FX Department.
Zhichao Li是英特尔的高级软件工程师，专注于分布式机器学习，尤其是Spark上的大规模分析应用和基础架构。他也是一名Spark项目的积极贡献者。 在加入英特尔之前，Zhichao曾在摩根士丹利的外汇部工作。
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