Blog-on-Digital-Transformation

Posts Tagged ‘Machine Learning’

Kubeflow: Automating Deployment of TensorFlow Models on Kubernetes

April 6, 2018 | 0 Comments | Sophia Turol
Learn how the Kubeflow project facilitates deployment of TensorFlow-based models locally, on premises, or in the cloud.

Building Recommenders with Multilayer Perceptron Using TensorFlow

March 5, 2018 | 0 Comments | Sophia Turol
This blog post explores the techniques to improve recommendations using matrix factorization, multilayer perceptron, negative sampling, etc. with TensorFlow.

Automotive Insurance with TensorFlow: Estimating Damage / Repair Costs

February 28, 2018 | 4 Comments | Sophia Turol
Learn how AI tools, such as TensorFlow and Keras, can help insurers to automate damage assessment and avoid overcharging by a car parts supplier.

Top 6 Enterprise IT Trends to Watch in 2018

January 3, 2018 | 0 Comments | Roger Strukhoff
What has changed since the last year and what has stayed the same?

Digital Twins for Aerospace: Better Fleet Reliability and Performance

August 3, 2017 | 0 Comments | Carlo Gutierrez...
Aerospace is going beyond connected machines. Digital twins enable the industry to save resources with prescriptive and predictive analytics.

Cloud Foundry Service Broker for GCP: What’s in It for Machine Learning?

July 17, 2017 | 0 Comments | Sophia Turol
A Cloud Foundry service broker for Google Cloud Platform enabled developers to access a variety of APIs and services. This session reviews some of them.

Artificial Intelligence Can Be a Catalyst Across Most Cycles of the IoT

With the challenges outlined, this blog post highlights the six stages of an IoT workflow where AI can help.

TensorFlow for Recommendation Engines and Customer Feedback Analysis

June 28, 2017 | 0 Comments | Sophia Turol
Learn how TensorFlow and Google Cloud Machine Learning help to find and recommend products, as well as analyze customer feedback in e-commerce.

Adopting TensorFlow for Manufacturing and Industrial Internet of Things

June 23, 2017 | 0 Comments | Sophia Turol
At TensorBeat 2017, a panel revealed the reasons behind TensorFlow adoption, exemplified real-life scenarios, and questioned the future of data.

Logical Graphs: Native Control Flow Operations in TensorFlow

June 22, 2017 | 0 Comments | Sophia Turol
This blog post explains how to create graphs with built-in logical branching structure so as to avoid extra complexity of the Python code.
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