Using a machine learning model’s own predictions on unlabeled data to add to the labeled data set sometimes improves accuracy, but not always
Stories by Martin Heller
AutoML frameworks and services eliminate the need for skilled data scientists to build machine learning and deep learning models
Unsupervised learning is used mainly to discover patterns and detect outliers in data today, but could lead to general-purpose AI tomorrow
Machine learning uses algorithms to turn a data set into a predictive model. Which algorithm works best depends on the problem
Not every problem can be solved by machine learning, and not every company is poised to apply AI. Here’s how to know whether your IT organization is ready to reap the benefits of artificial intelligence.
Big data, machine learning, data science — the data analytics revolution is evolving rapidly. Keep your BA/BI pros and data scientists ahead of the curve with the latest technologies and strategies for data analysis.
GPUs in the cloud put the predictive power of deep neural networks within reach of every developer
A few years ago I was the CTO and co-founder of a startup in the medical practice management software space. One of the problems we were trying to solve was how medical office visit schedules can optimize - everyone's - time. Too often, office visits are scheduled to optimize the physician's time, and patients have to wait way too long in overcrowded waiting rooms in the company of people coughing contagious diseases out their lungs.
From 3D views to managed provisioning processes, there’s a lot for Android app developers to love about Lollipop
From full-blown IDEs to essential resource utilities, these Android apps bring powerful programming features to phones and tablets