CatBoost Machine Learning framework from Yandex boosts the range of AI
This is the year artificial intelligence (AI) was made great again. AI is all about machine learning, and machine learning is all about deep learning (DL), according to the hype. For connaisseurs like Yandex, there’s more to AI than deep learning. CatBoost, the open source framework Yandex just released, aims to expand the range of what is possible in AI and what Yandex can do.
It’s hard to avoid the AI buzz out there. Beyond the hype, there’s no denying that progress is done in leaps and strides. We are in mid-2017, and already the image of machine intelligence as painted for 2016 has seen notable new entries.
Just keeping in the technology stack, we have seen the introduction of Caffe2 from Facebook, Core ML just out from Apple, which has entered the game, and let’s not forget the widely ambitious NeoPulse.
One thing all of these have in common: Deep learning. Caffe2 and NeoPulse are exclusively DL frameworks, and DL is also central to Core ML. While DL is certainly valuable, there is more to ML. And there are also more players in the game than the usual suspects.
Meet CatBoost, a new ML library based on gradient boosting (GB) and aiming to find its own sweet spot in the AI landscape.