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Predicting with GCP

Giulia
April 24, 2019

Predicting with GCP

20 minutes presentation for Women in Machine Learning & Data Science Paris meetup.

With the release of Google Cloud AutoML, Google Cloud Platform provides yet another out-of-the-box AI managed service. But this doesn’t mean that data scientists have no say in training and deploying customised machine learning models in the cloud. There are services, such as Cloud ML Engine, devoted to this specific goal.

Giulia

April 24, 2019
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  1. @Giuliabianchl • Set up a GCP account (gmail ID needed)

    • Sign in Google Cloud Console and set up a project ($$$) • Install Cloud SDK Google Cloud Platform
  2. @Giuliabianchl • Cloud → managed services • From "on-premises" to

    *aaS ◦ IaaS ◦ PaaS ◦ SaaS • Access to theoretically unlimited resources • Rapidity of provisioning • Reliability Cloud what ?! And why should I even care?
  3. @Giuliabianchl Prediction pipeline Input new data Feature engineering Predict! Model

    deployed in RPi Prediction saved in RPi Done in 45 sec.
  4. @Giuliabianchl Prediction pipeline Input new data Feature engineering Predict! Model

    deployed in GCP Prediction saved in GCP Done in 5 sec.
  5. @Giuliabianchl ... has a huge potential for data scientists ...

    is not fully data scientist friendly yet ... it needs more documentation ... evolves super fast Google Cloud Platform...