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This document discusses using machine learning and cloud services to gain insights from data. It provides an overview of cloud services including virtual machines, file storage, machine learning APIs, and serverless services. It also discusses using tools like Google Cloud Platform and Google Vision API for advanced analysis of structured and unstructured data. Management of cloud resources can be done through web user interfaces and scripts to connect different components for building machine learning models.

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Getting insights Intelligent Analysis in the Cloud
Machine Learning Cloud My last 11 years PhD and research Analyst ML Specialist Became Data Engineer on Google Cloud Platform
What Where Why How
What
Your Cloud providers
What is in the Cloud
What is in the Cloud Virtual Machines File storage ML APIs Data processing Serverless services Databases
Where Why How What
Where
Google Analytics takes you a long way
Automatic data activation Analysis of unstructured data Advanced analysis Beyond GA
Advanced analysis
Datalake
Analysis of unstructured data (text, images, audio & video)
Text Analysis
Automatic data activation
Intelligent Prefetching /home /about /cases /about /cases
Where Why How What
Why
Optimal hardware & usable services
Scalability Q1 2017 Q2 2017 Q3 2017 Q4 2017 Q1 2018 Q2 2018
Where How What Why
How
Management on Web UI
Management on Web UI Tools Projects Errors Usage Cost
https://cloud.google.com/vision/
https://cloud.google.com/vision/
https://cloud.google.com/vision/
Scripts to connect components
Road ahead: no scripting? Data prep Auto ML
WhereWhat Why How
GA is not enough One-stop tool shop HW can be boring & messy UI & scripts
Copenhagen Artillerivej 86 2300 København S +45 70 20 29 19 Stockholm Strandvägen 7A 114 56 Stockholm +45 70 20 29 19 London 43A Southend Road BR3 1SP. London +45 70 20 29 19 Oslo CJ Hambros plass 2 N-0164 Oslo +45 70 20 29 19 Thank you! Héctor P. Martínez hector@iihnordic.com in/hectorpmartinez

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