Three Approaches to Testing and Validating TensorFlow Code
Read about some assertion methods that may help to validate data shapes, graph structures, and numerical calculations of the TensorFlow code.
Natural Language Processing Saves Businesses Millions of Dollars
Here, we overview some scenarios and the means of machine learning that help to automate operations, enable time efficiency, cut overhead costs, etc.
Things That Matter When Building a Natural Language Chatbot
Chatbots help to automate communication, streamline operations, get customer feedback, etc. Below are some recommendations for building a chatbot.
Approaches and Models for Applying Natural Language Processing
Natural language processing is actively used to recognize patterns, make predictions, produce content, reconstruct 3D models, etc.
Analyzing Satellite Imagery with TensorFlow to Automate Insurance Underwriting
Paired with image classification models, TensorFlow can help to analyze satellite / aerial / street view imagery of buildings to deliver risk-related details of property.
Kubeflow: Automating Deployment of TensorFlow Models on Kubernetes
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
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
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
What has changed since the last year and what has stayed the same?
Digital Twins for Aerospace: Better Fleet Reliability and Performance
Aerospace is going beyond connected machines. Digital twins enable the industry to save resources with prescriptive and predictive analytics.
