Global Data Science Forum

OpenAI is an independent research group who has led the AI community in an assortment of projects ranging from NLP to RL. Their decision to standardize on PyTorch as their Deep Learning framework is a noteworthy endorsement in the ongoing debate for organizations considering using either TensorFlow or PyTorch. Does their choice sway you in planning future projects?

AutoML is a term that appears increasingly in tech industry articles, and vendor product claims, and is also a hot topic within AI research in academia. This article introduces the ideas behind AutoML as well as resources to keep up to date with progress in the space. Read more

GitHub is using ML to make it easier for people to contribute to Open Source Software projects. Comfort in contributing to open source is an essential skill for any data scientist looking to build up their resume. Read more

Federated Learning is a practice in which datasets stored in different places, even behind multiple competitors firewalls, are used to train the same model. This article walk through applications using the FL framework. Read more

Google did not publish 25 million free data sets, but it did release a free tool for searching 25 million publicly available datasets. These datasets may or may not be free, as it has indexed any data set published using the open standards of schema.orgwhich for profit data providers are using too. Read more

From automated irrigation systems to precision agriculture and animal health monitoring, ML is transforming the way farming is done today. Read more

There are 6 research papers named from the NeurIPS Conference chairs as being exceptional and worth reading. Have you made it through them yet? Read more

Amazon has established Deep Reinforcement Learning (DRL) benchmarks for Logistics/OR Tasks. The three canonical dynamic resource allocation problems they've measured: Bin Packing, Newsvendor, and Vehicle Routing. Read more