AI-based stock trading, a record-breaking competition on Kaggle and more stories cherry-picked from all the interesting ML- and AI-related news from September.
About Konrad Budek
This author has yet to write their bio.Meanwhile lets just say that we are proud Konrad Budek contributed a whooping 14 entries.
Entries by Konrad Budek
Reinforcement learning is gaining notice as a way to train neural networks to solve open problems that require a flexible, creative approach. As a huge amount of computing power and time are required to train reinforcement learning agent, it is no surprise that researchers are looking for ways to shorten the process. Expert augmented learning […]
It was far and away the most popular Kaggle competition, gaining the attention of more than 8,000 data scientists globally. The team of Paweł Godula, team leader and deepsense.ai’s Director of Customer Analytics, Michał Bugaj and Aliaksandr Varashylau took fifth place and 1st on the public leaderboard.
Deloitte estimates that in 2021 enterprise spending on artificial intelligence and machine learning projects will reach 57 billion dollars
For companies seeking ways to test AI-driven solutions in a safe environment, running a competition for data scientists is a great and affordable way to go – when it’s done properly. According to a McKinsey report, only 20% of companies consider themselves adopters of AI technology while 41% remain uncertain about the benefits that AI […]
Adding programming skills to the data analyst’s skill set can go a long way to making the perfect data scientist.
Child’s mind is able to create fantastic worlds in seconds. So what would happen if robots had an artificial imagination?
German team – the one Goldman Sachs picked with predictive analytics as the probable world champ – failed to get out of its group for the first time in 80 years.
Although machine learning is seen as a monolith, this cutting-edge technology is diversified, with various sub-types including machine learning, deep learning, and the state-of-the-art technology of deep reinforcement learning.
Software that understands muscle-controlled limb movement would be able to translate neural signals into instructions for automated arms or legs.