TL;DR: authors propose a DenseNet-like ensemble of decision trees, trained end-to-end by backpropagation and beats both xgboost and neural networks on heterogeneous ("tabular") data. Nowadays, deep neural networks (DNNs) have become the main instrument for machine learning tasks within a wide range of domains, including vision, NLP, and speech. Meanwhile, in an important case of heterogenous tabular data, the advantage of DNNs over shallow counterparts remains questionable. In particular, there is no sufficient evidence that deep learning machinery allows constructing methods that outperform gradient boosting decision trees (GBDT), which are often the top choice for tabular problems. In this paper, we introduce Neural Oblivious Decision Ensembles (NODE), a new deep learning architecture, designed to work with any tabular data.

Chatbots are computer programs that simulate human speech through voice commands and or text chat.

Sweden-based telecom device manufacturer Ericsson has bought the workforce Niche AI for its Bengaluru-based artificial intelligence centre.

Half-price cinema tickets, cycle to work schemes and gym passes have long been part of employee benefits programmes. But with research showing 84% of millennials look to leave their jobs within the first two years, employers want to tailor their perks packages to their employees' needs. Emerging technologies such as data analytics, chatbots, and wearables can help employers know which benefits resonate with employees. And machine learning can monitor take-up and avoid wasting money on unwanted benefits. "From an employer perspective, there is already a lot more emphasis on looking at data to see what benefits employees are using," says Jeanette Makings, head of financial education at merchant bank Close Brothers.

Deliver data-driven results and predict the future by building machine learning models that change every aspect of your business. This 3-day course provides the building blocks of machine learning so students can improve revenue, reduce costs, create new opportunities and learn essential skills for this high-demand field.

In reality, ML is just another form of learning from examples. Whether it's a human or machine that's learning to perform a task, all that matters is the …

"I'm not an alarmist when it comes to machine learning, but I fear that something terrible happens and there won't be a group of people who can …

Machine learning helps computers analyze data and learn what to do, so that they don't have to be programmed to perform each task.