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Advanced ML: ML Infrastructure

Advanced 5 Langkah 5 jam 33 Kredit

Machine Learning is one of the most innovative fields in technology, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, GCP has a tool for just about any machine learning job. In this advanced-level quest, you will get hands-on practice with machine learning at scale and how to employ the advanced ML infrastructure available on GCP.

Data

Quest Outline

Lab Praktik

Real Time Machine Learning with Google Cloud ML

Using Cloud DataProc running on a Hadoop cluster you will analyse a data set using Bayes Classification.

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Lab Praktik

Scikit-learn Model Serving with Online Prediction Using AI Platform

In this lab you will build a simple scikit-learn model, upload the model to AI Platform Prediction, and make predictions against the model.

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Lab Praktik

Distributed Machine Learning with Google Cloud ML

Learn the process for partitioning a data set into two separate parts: a training set to develop a model, and a test set to evaluate the accuracy of the model and then independently evaluate predictive models in a repeatable manner.

Deutsch English español (Latinoamérica) français 日本語 português (Brasil)
Lab Praktik

Real Time Machine Learning with Google Cloud ML

Using Cloud DataProc running on a Hadoop cluster you will analyse a data set using Bayes Classification.

Deutsch English español (Latinoamérica) français 日本語 português (Brasil)
Lab Praktik

Awwvision: Cloud Vision API from a Kubernetes Cluster

This hands-on lab uses Kubernetes and Cloud Vision API to create an example of how to use the Vision API to classify (label) images from Reddit’s /r/aww subreddit and display the labelled results in a web app.

Deutsch English español (Latinoamérica) français 日本語 português (Brasil)

Daftar Sekarang

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