Tag: Data Science

BigQuery Data Science Data Studio June 24, 2019

From College to the Pros with Google Cloud Platform (Part 1) - Getting together and analyzing NBA players stats.

Data Science GCP Certification June 24, 2019

10 Days to Become a Google Cloud Certified Professional Data Engineer - Overview of resources used for Data Engineer exam preparation.

Data Science R June 24, 2019

From College to the Pros with Google Cloud Platform (Part 2) - The second part of NBA players analysis.

Data Science Google Cloud Dataproc June 17, 2019

Scale out RAPIDS on Google Cloud Dataproc - Scaling GPU data jobs on Cloud Dataproc.

BigQuery Data Science GCP Experience June 17, 2019

Analytics at lightspeed with Google BigQuery - The article describes how Aditya Birla Group created a digital platform on GCP to manage the travel of their employees.

Data Science June 17, 2019

Setup Julia with Jupyter notebook on Google Cloud Platform - Tutorial on how to set up and use Julia on Jupyter notebooks hosted on GCP.

Data Science Security June 10, 2019

How to use cloud storage to securely load data into Neo4j - Methods for loading data into a remote Neo4j Instance — Part 2

Apache Beam Data Science Google Cloud Dataflow Python May 13, 2019

Let’s Build a Streaming Data Pipeline - Creating Apache Beam / DataFlow pipeline to parse web server logs.

Data Science GCP Certification May 13, 2019

Passing the (new) Google Professional Data Engineer exam within 7 weeks - Experience of preparing and taking Data Engineer certification.

Data Science April 15, 2019

How to get started with Google Colab and Kaggle - Example of using Colab for Kaggle competitions.

AI Data Science Machine Learning April 8, 2019

GCP Notebook Executor v0.1.2 - Executing long running Jupyter Notebook jobs on GCP.

BigQuery Data Science Google Cloud Dataflow Google Cloud Dataprep Machine Learning TensorFlow April 8, 2019

End-to-end churn prediction on Google Cloud Platform - Overview of GCP architecture to build customer churn prediction compromising of data acquisition, data wrangling, modeling, model deployment, and a business use case.

 

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