Google Cloud Big Data and Machine Learning Blog

Innovation in data processing and machine learning technology

Using machine learning for insurance pricing optimization

Wednesday, March 29, 2017

Global insurance company AXA used machine learning in a POC to optimize pricing by predicting “large-loss” traffic accidents with 78% accuracy.

Analyzing customer feedback using machine learning

Tuesday, March 28, 2017

How Wootric's platform uses Google Cloud Natural Language API to complement its own machine learning to save on infrastructure and engineering costs.

Announcing general availability of Google Cloud Dataflow for Python

Thursday, March 23, 2017

Google Cloud Dataflow is now generally available for Python. Pipelines built using Apache Beam for Python can use Cloud Dataflow's advanced features.

Google Cloud Platform for Data Scientists: Using R with Google Cloud SQL for MySQL

Wednesday, March 22, 2017

By connecting R to Cloud SQL, you can take advantage of all R features on top of a scalable, fully-managed MySQL service.

Monitoring and improving your Google Cloud Dataflow pipelines with Google Stackdriver

Thursday, March 16, 2017

Learn how to use Google Stackdriver to monitor, chart and create alerts for Google Cloud Dataflow jobs.

Google Cloud Next '17 data, analytics and machine learning session video now online

Wednesday, March 15, 2017

Watch the keynote by Fei-Fei Li, Chief Scientist, Google Cloud AI and ML and explore all session video about data analytics and machine learning

Google Cloud Platform adds new tools for easy data preparation and integration

Thursday, March 9, 2017

New support for integrated data preparation and integration services will help customers get faster value from data analytics

Announcing Google Cloud Video Intelligence API, and more Cloud Machine Learning updates

Wednesday, March 8, 2017

Today we announced new products, research and education programs to ensure machine learning is accessible to all businesses, data scientists & developers

Data Science on the Google Cloud Platform: the first book

Thursday, March 2, 2017

This upcoming O’Reilly Media book is the first one dedicated to doing data science on the modern public cloud

Jeff Dean on machine learning, part 3: how machine learning is being used at Google

Wednesday, March 1, 2017

Jeff explains how machine learning is being used inside Google, what resources Google offers to developers, and how you can get started.

Combining Thomson Reuters data with Google BigQuery and Google Cloud Pub/Sub API

Tuesday, February 28, 2017

We parnered with Thomson Reuters to demonstrate the benefits of combing Google's core data technologies with Thomson Reuters financial market content.

Google Cloud Platform for data scientists: using Jupyter Notebooks with Apache Spark on Google Cloud

Monday, February 27, 2017

Using the combination of Jupyter Notebooks and GCP gives you a familiar data science experience without the tedious infrastructure setup

Using Google Cloud Machine Learning to predict clicks at scale

Tuesday, February 21, 2017

Learn how Google Cloud Machine Learning and TensorFlow make it easy to train models on very large amounts of data

Adding machine learning to a serverless data analysis pipeline

Tuesday, February 21, 2017

In the right architecture, machine-learning functionality takes data analytics to the next level of value.

5 can’t-miss sessions about machine learning at Google Cloud NEXT ‘17

Thursday, February 16, 2017

As reflected in the conference agenda, implementation of machine learning across all kinds of apps is a major focus at Google Cloud NEXT ‘17.

Google Cloud and YouTube-8M Challenge: Predict YouTube video tags for a chance to win up to $30K

Wednesday, February 15, 2017

Learn about the Google Cloud and YouTube-8M Challenge on Video Understanding.

Jeff Dean on machine learning, part 2: TensorFlow

Monday, February 13, 2017

Jeff Dean talks about TensorFlow, the machine learning toolkit open sourced by Google.

Crowning the rat capital of New York: importing data for analysis with Google BigQuery

Thursday, February 9, 2017

In this installment of #TILwBQ, import a new table into BigQuery to investigate the increase in rat complaints in the open NYC dataset.

The book for getting hands-on with machine learning, deep learning and TensorFlow

Tuesday, February 7, 2017

This new book from YouTube’s former video-classification lead introduces readers to concepts as well as practical implementations of deep learning.

5 can’t-miss sessions about big data and analytics at Google Cloud NEXT ‘17

Monday, February 6, 2017

For data engineers, scientists, and analysts, Google Cloud NEXT ‘17 is a required stop on the conference circuit.

Four seasons in one post: using Google BigQuery to explore weather effects on NYC

Thursday, February 2, 2017

With over 150GB of New York City public data, parsing for patterns and insights is a challenge. Learn how to use the CORR function to find correlations.

Jeff Dean on machine learning, part 1: surveying the landscape

Wednesday, February 1, 2017

Google Senior Fellow and leader of the Google Brain research team, Jeff Dean, describes the current landscape of machine learning past, present and future

Understanding cost-versus-speed tradeoffs in Google Cloud Dataflow batch pipelines

Tuesday, January 31, 2017

Grasping the trade-offs between cost and speed is the first step in improving the efficiency of your data pipelines

How to run a terabyte of Google BigQuery queries each month without a credit card

Wednesday, January 25, 2017

New to BigQuery and interested in playing with our public datasets? You can process your first terabyte of data, every month, at no cost.

Scaling exactEarth’s satellite vessel-tracking service using GeoMesa on Google Cloud Platform

Monday, January 23, 2017

Google Cloud Bigtable, Google Cloud Dataproc and GeoMesa are the main components in this solution for global geospatial analytics

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