BigDL: Integrating Deep Learning with Apache Spark
Section: Full talk Technical level: Beginner
BigDL (https://github.com/intel-analytics/BigDL/) is an open source distributed deep Learning library, which is natively integrated with Apache Spark and provides rich deep learning functionalities for Spark. It combines the benefits of “high performance computing” and “Big Data” architecture, so as to provide orders of magnitude speedup than existing out-of-box open source DL frameworks (e.g., Caffe/Torch/Tensorflow) on single-node Xeon, and efficient scale-out based on the Spark architecture. In this talk, we will showcase how to users can easily build deep learning powered Big Data analytics using BigDL together with other libraries on Spark.
BigDL use case
BigDL demo (if possible)
Mukesh Gangadhar works as a senior performance architect at Intel. He is focused on improving the efficiency of running software applications on Intel based platforms.
Deep Learning with High School Math (or Less)
You don’t need a PhD or a master’s degree or even a bachelor’s degree in Math/CS to learn and appy deep learning. In most cases, all you need is some programming experience and a quick revision of some high school math e.g. differentiation and matrix multiplication. I’ll show you how you can get up and running in just few hours, and build state of the art deep learning models that solve problems … more