The primary goal of this blog post is to provide technical information on the addition of tree-based machine learning (ML) algorithms to Einstein Discovery in the Summer ’20 Release. This article helps readers understand the capabilities, benefits, and details of ensemble (tree-based) algorithms in Einstein Discovery. Tree-based algorithms go beyond Einstein Discovery’s traditional focus on ...
In order to satisfy increasingly diversified customer demands, product and service portfolios are steadily becoming larger. B2B and B2C companies are expected to guide their customers to the best fitting bundle in their large panoply of products. Predicting the likelihood of a customer or prospect purchasing a particular product is essential and requires a deep ...
The accuracy of Machine Learning models gives rise to one of the most confusing discussions in the world of Machine Learning. There are multiple reasons for that. First, many different performance metrics are used, which makes fair comparisons and transparent discussions hard. Secondly, expectations are often unrealistically high, caused by extremely overblown media coverage of ...
You created a story in Einstein Discovery. You measured its model’s accuracy. Then you made some necessary improvements. The model you deployed is now bringing predictions and recommendations right to your users’ fingertips. You’re pretty satisfied with what you achieved. Cool, you’re done. Your model is out in the wild now. Onto the next adventure, ...
Einstein Discovery is AI-powered analytics that enables business users to automatically discover relevant patterns based on their data – without having to build sophisticated data models. However, Einstein Discovery is only as good as the historical data it is analyzing. Wrangling the data, which is always the hardest part, involves cleaning and consolidating your historical ...
So far in this series we have introduced the notion of Einstein Analytics Stories, why you may create one and from a high level what sorts of business problems and analyses you can approach using a Story. But, we’re sure you are aware, Stories are just part of the business problem you are tackling – ...
Before getting started with creating first your Einstein Analytics Plus Stories, there are some things you need to think through and decide. Typically people are concerned about data, but we will save that for later. But even before rolling up your sleeves and finding and crunching data, the most important pre-creation task is the need ...
When I started working with Einstein Analytics in 2015 needless to say not many knew much about Einstein Analytics. In the past couple of years, the DataTribe as we call it has emerged and we have grown in numbers. I find many more being knowledgeable on Einstein Analytics in terms of visualization and data prep, ...
Einstein Discovery accelerates the embedding of augmented analytics in a business user’s work environment. The predictive models are created by the platform using a “No Code AI Approach”, which means that the algorithms to train these models are part of the solution, and don’t need to be coded by advanced developers or data scientists. To ...
As artificial intelligence, and specifically machine learning, is conquering today’s business world, a new way of human machine interaction enters our professional lives. We are more and more guided by predictive models that prioritise our work and give recommendations to improve our business. Once widely adopted, this embedding of so-called augmented analytics can bring tremendous ...