Businesses are generating data at a faster pace than ever: 90% of the world’s data was generated within the last two years. The increased data volume is rapidly outpacing our ability to consume it.

Machine learning enables AI to learn and improve without direct programming. AI uses machine learning to analyze vast data sets and identify patterns. Accuracy of AI predictions depends on quality ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

Xiangrui Meng of Databricks, a committer on Apache Spark, talks about how to make machine learning easy and scalable with Spark MLlib. Xiangrui has been actively involved in the development of Spark ...

Read more about how machine learning and deep learning differ, where each is used, and how businesses choose between them in ...

In some ways, Java was the key language for machine learning and AI before Python stole its crown. Important pieces of the data science ecosystem, like Apache Spark, started out in the Java universe.

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...