Google Cloud Big Data and Machine Learning Blog

Innovation in data processing and machine learning technology

Practice makes perfect: the Professional Data Engineer Practice Exam is now live

Wednesday, February 14, 2018

Google Cloud Certified now offers an online practice exam designed to help Professional Data Engineer exam takers check their test readiness.

Easy distributed training with TensorFlow using tf.estimator.train_and_evaluate on Cloud ML Engine

Friday, February 9, 2018

Learn how to quickly and simply distribute your training workload with TensorFlow 1.4 and Cloud Machine Learning Engine.

Bitcoin in BigQuery: blockchain analytics on public data

Thursday, February 8, 2018

Learn how to access the Bitcoin blockchain via a new public Google BigQuery dataset. Learn how to visualize transactions in Google Data Studio.

How to process weather satellite data in real-time in BigQuery

Wednesday, January 31, 2018

Learn how to analyze historical GOES-16 geostationary weather satellite data in BigQuery, and visualize a real-time feed, to understand weather events.

Updating Cloud Dataproc for faster speeds and more resiliency

Friday, January 26, 2018

Cloud Dataproc now allows you to designate 3 master nodes for resiliency, and you can now assign persistent SSDs for added speed.

Keys to faster sampling in Cloud Dataflow

Wednesday, January 24, 2018

Learn how to sample faster in Cloud Dataflow in a new white paper, which focuses on building a composite transform, while preserving specific attributes.

A guide to machine learning for the chronically curious: ML Explorer

Monday, January 22, 2018

Introducing the ML Explorer series, which provides a tour of the machine learning landscape for application developers who want to build ML using APIs.

Problem-solving with ML: automatic document classification

Wednesday, January 10, 2018

Learn how to build a machine learning-based document classifier by exploring this scikit-learn-based Colab notebook and the BBC news public dataset.

Improving the efficiency of your helpdesk with serverless machine learning

Thursday, December 28, 2017

Learn how to augment user-submitted data in helpdesk tickets to reduce completion time, using the Natural Language Processing API and Cloud ML Engine.

Busting 12 myths about BigQuery

Friday, December 22, 2017

From our experience with a variety of customers, both enterprises and startups included, we debunk 12 common BigQuery myths.

New in TensorFlow 1.4: converting a Keras model to a TensorFlow Estimator

Monday, December 18, 2017

Learn how to convert a Keras model into a TensorFlow Estimator, using a text classifier as an example. This conversion is newly possible in TensorFlow 1.4.

Bringing Cloud ML Engine to more developers with online prediction features and reduced prices

Thursday, December 14, 2017

We're announcing price reductions for Google Compute Engine GPU instances and Cloud ML Engine while enabling online prediction as a service.

Real-time forecasts in the cloud: from market feed capture to ML predictions

Thursday, December 14, 2017

Learn how to set up a price prediction engine using the Thomson Reuters FX live data feed, the TensorFlow Estimator object, and Cloud Datalab.

Drawings in the Cloud: introducing the Quick, Draw! dataset

Friday, December 8, 2017

After Quick, Draw! has captured over a billion doodles, a dataset of 50 million drawings is now available in BigQuery and Cloud Datastore.

Analyzing tweets using Cloud Dataflow pipeline templates

Wednesday, December 6, 2017

Learn how to use App Engine and Cloud Dataflow jobs to analyze a data stream of tweets, then store them in BigQuery.

Cloud Video Intelligence and Cloud Natural Language Content Classification are now generally available

Tuesday, December 5, 2017

Cloud Video Intelligence and Cloud Natural Language Content Classification are now generally available.

Building a better GIPHY with Google Cloud’s machine learning tools

Tuesday, December 5, 2017

GIPHY's Director of Engineering explains how GIPHY uses Cloud Vision and NLP APIs to create better machine learning-derived captions for their GIFs.

Focus on Security: BigQuery announces support for customer managed encryption keys and custom roles for Identity Access and Management

Monday, December 4, 2017

BigQuery now includes new security-focused features, including the Cloud Key Management Service, beta custom roles for IAM, and sorting options.

Analyzing text in a Google Sheet using Cloud Natural Language API and Apps Script

Friday, December 1, 2017

Try out Apps Script on a Google Sheet populated with a Kaggle Dataset: interpret with Cloud Natural Language, and visualize the output in DataStudio.

Google Cloud provides a unified, streamlined way to execute your ML strategy

Thursday, November 30, 2017

BigQuery lets you devise and apply a robust machine learning strategy to your data, using Dataprep, ML Engine, Dataflow, and Datalab.

Separation of storage and compute in BigQuery

Wednesday, November 29, 2017

BigQuery permits you to separate storage from compute, allowing you to scale both independently. Learn the advantages to keeping your data serverless.

Using Apache Spark with TensorFlow on Google Cloud Platform

Tuesday, November 28, 2017

Google Cloud provides managed services for Apache Spark and TensorFlow, called Cloud Dataproc and Cloud ML Engine, respectively. Learn how they integrate.

Cloud OnAir shows you how to get ML-derived insight out of your data

Monday, November 20, 2017

Learn to apply machine learning to your data at Cloud OnAir: The Journey from Big Data to AI, an online event comprising of a series of webinars, Q&As.

Announcing BigQuery Data Transfer Service general availability

Thursday, November 16, 2017

BigQuery Transfer Service, newly available, allows you to ship data to BigQuery within 24 hours of arrival, according to the Data Delivery SLA.

How to integrate Dialogflow with Chatbase for easier bot analytics

Thursday, November 16, 2017

Build better conversational experiences with Dialogflow and Chatbase, for voice or text chatbots.

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