Over a month after SQL Server 2019 became generally available, Microsoft has now shined light on some more aspects of the improved machine learning capabilities offered with this release.

By taking advantage of tools like Amazon QuickSight, Aurora and Athena in combination with SQL queries, developers can have much more direct access to machine learning models and underlying data ...

The machine learning pipeline (credit: Pin-Yu Chen) Adversarial attacks that are unique to the training phase include data poisoning and backdoors. In data poisoning attacks , the attacker inserts ...

But it was SQL Server’s new machine learning tools that grabbed my attention. Machine learning remains one of Microsoft’s big themes for 2017, and it’s an important segment of SQL Server 2017.

Databricks identified several of the fastest-growing areas in the Spark ecosystem as Spark SQL users (up 67 pecrent), streaming users (up 57 percent) and advanced analytics users (leveraging the ...

Google BigQuery is making it possible for data analysts to deploy machine learning (ML) models using only simple SQL statements, potentially reducing the ML skills gap. By Pam Baker August 2, 2018 ...

Then they gave another developer the same task, except this person was using Amazon Machine Learning. Jassy claimed he was able to achieve the same 92 percent accuracy in just 20 minutes.

Python has reached 7 million active developers and is closing in on Java in terms of popularity, thanks to 62 percent of machine learning developers and data scientists who now use Python. DevOps has ...

Stack Overflow releases its annual Developer Survey Results, which finds DevOps and machine learning are the top most important trends in the industry right now. Toggle navigation.

The latest trends in software development from the Computer Weekly Application Developer Network. Professor Clough argues that the adoption of Machine Learning (ML) and Artificial Intelligence (AI ...