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AI Boot Camp Overview: Build/Operate Deep Learning Data Pipeline & Data Lake Cloud/Container Cluster w/t TensorFlow/Spark/Hadoop in API(Python)/CLI(Bash)

Event status: Canceled
This event will not appear on the public calendar until it has been approved. If this does not happen soon, contact [email protected] for assistance.

Setup Time:
15 minutes
Saturday, April 1, 2017 at 2:00pm
Saturday, April 1, 2017 at 4:00pm
Teardown Time:
15 minutes
Estimated size:
Large Event Room

You go to a lot of trainings and/or meetups, whether free or not, expensive or cheap, ALL of those are either marketing fluff, sales pitches, or short of global business pictures, or lack of technical details, no insight, let alone foresight. Our 2-hr Cream-Boot Camp is radically different, vendor agnostic, no strings attached, full of meat, lots of demos, offering you both macro & micro perspective of the state-of-the-art in practical way with hindsight, insight and foresight!]

Overview of the following 2-Day Boot Camp- Build & Operate Deep Learning Data Pipeline & Data Lake Cloud/Container Cluster with TensorFlow, Spark & Hadoop in API (Python) or CLI (Bash)

What you'll learn, and how you can apply it
• Learn how Machine & Deep Learning AI Big Data Cloud enables data scientists to help companies reduce costs, increase profits, improve products, retain customers, and identify new opportunities.
• Topics include:
 How to identify potential business use cases in leveraging big data cloud AI technology
 How to obtain, clean, and combine disparate data sources to create a data pipeline for data lake
 What Machine-Learning (Shallow Learning) & Deep Learning technique to use for a particular data science project
 How to conduct PoC & productionalized big data projects in cloud/container cluster at scale
 How to create real-time data pipelines using the latest open source with public cloud or private cloud/container, ingest data in real time and at scale, process the data in real-time/interactive/batch, and build data products from real-time data sources
 How to combines ETL, batch analytics, real-time stream analysis with machine learning, deep learning, and visualizations through both data pipeline & data lakes
 Understand & master TensorFlow's fundamentals & capabilities
 Explore TensorBoard to debug and optimize your own Neural Network Architectures, train, test, validate & serve your models for real-life Deep Learning applications at Scale.

By: Yang Zhang <[email protected]>
For more info, you might check the following links:
- www.tinyurl.com/AIBootCamp (Full Boot Camp I: 3/11-12)
- www.tinyurl.com/AIBootCamp2 (Full Boot Camp II: 3/25-26)
- www.hwswworld.com/aibootcampoverview3.pdf - Prev. Talk Slides
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