Machine learning is a branch of artificial intelligence that includes methods, or algorithms, for automatically creating models from data. Unlike a system that performs a task by following ...

In the current era of big data, the volume of information continues to grow at an unprecedented rate, giving rise to the crucial need for efficient ...

The data-driven revolution is prefaced upon the idea that data and algorithms can lead companies away from biased human judgement towards pristine mathematical perfection that captures the world ...

A team from Google Research has open-sourced Model Search, an automated machine learning (AutoML) platform for designing deep-learning models. Experimental results show that the system produces ...

Developing AI applications is much different than the traditional app dev lifecycle. Machine learning models and step replication are two main areas data scientists and engineers need to be aware of ...

Machine learning uses algorithms to turn a data set into a model that can identify patterns or make predictions from new data. Which algorithm works best depends on the problem.

Once an algorithm is trained on massive datasets to recognize patterns, make decisions, and generate insights, it becomes an AI model. The more data it has been trained on, the more accurate it is.

AI is thought to be only data-driven these days. Let's take a balanced look at AI over time and consider algorithms and process.