How IT pros might learn to believe in AI-driven network-management
Explainable AI might overcome the distrust that enterprise network engineers have for AI/ML management tools that have the potential to streamline network operations.
Explainable AI might overcome the distrust that enterprise network engineers have for AI/ML management tools that have the potential to streamline network operations.
The new updates to Google Cloud’s machine learning service will help the company square up against rivals such as Microsoft, AWS and IBM.
Kaskada, acquired by DataStax in January, offers an open-source based unified events processing engine aimed at helping enterprises build real-time machine learning applications.
Changing assumptions and ever-changing data mean the work doesn’t end after deploying machine learning models to production.
The open source world is ripe with projects to support software development on the frontiers of artificial intelligence and machine learning.
Amazon DevOps Guru for Serverless uses machine learning to improve the operational availability and performance of AWS Lambda applications.
Cisco has added new features to its Intersight cloud management system, UCS X-Series server, and HyperFlex hyperconverged system.
New Relic has updated its One platform to import data from different systems, monitor ML application performance and retrain models.
At re:Invent, AWS unveiled updates to database, machine learning and serverless offerings designed to reduce complexity and cost.
Better testing means better software. Using NLP, test data generation, and optimised testing can quickly improve applications.
GCP is offering new data and machine learning tools designed to clear up data inefficiencies and ease application development for enterprises.
Data poisoning involves tampering with and polluting a machine learning model's training data, impacting the ability to produce accurate predictions.
From exploratory data analysis to automated machine learning, look to these techniques to get data science projects moving and to build better models.
While approaches and capabilities differ, all of these databases allow users to build machine learning models right where data resides.
Artificial intelligence and machine learning bring new vulnerabilities along with their benefits. Here's how several companies have minimized their risk.