MLflow is open-source software initially developed by DataBricks for managing the “machine learning lifecycle.” It makes the model artifacts and their environment specifications more readily available when assembling ML model applications or for other purposes such as collaborating with teammates
Natural language models have come a long way in the past couple of years. With the advent of the deep learning Transformer architecture, it became possible to generate text that could, plausibly, be passed off as written by a human.
Mosaic is developing a machine learning based tool that assists corporate travel manages and business travelers in making the safest travel decisions possible.
Working in conjunction with subject matter experts, data scientists can swiftly apply statistical tools and uncover emerging trends. This is extremely valuable for companies trying to operate in a disruption. Not only will executives have an accurate representation of their present situation, but new products & services can be devised from these insights.
Global external shocks are going to continue to happen, that is a fact of operating a business in today’s environment. As companies embrace data science in their decision-making processes, they are better positioned to deal with these disruptions, allowing them to manage a risk-optimized supply chain.
Designing and deploying computer vision is a powerful technology that humans can employ to improve their decision making. The only limits to these technologies lie within our ability to think of problems for them to solve.
Gameplay data are a trove of information about how athletes are acting and reacting in real situations, and there are real benefits to be gained by mining this information at every level, from the athlete to the entire team. In the modern age, the team that can measure and understand itself through its own data will have the competitive edge.