Our expert team specializes in developing tailor-made machine learning solutions that drive innovation and growth. With a proven track record of successful implementations across diverse industries, Mosaic Data Science has helped customers elevate their operations, stay ahead of the competition, and make data-driven decisions with our comprehensive machine learning development services.
We sat down with Senior Data Scientist Alex Tennant for his perspective on the opportunities and complexities of NLP and how Mosaic is paving the way for the consistent evolution of this powerful technology.
Network science and simulation provide a robust framework for the study of network systems in all their complexity.
Wielding the power of computer vision human action extraction to gain insights from video data presents an opportunity for logistics companies to make improvements for new and current customers.
As our world becomes more and more digitized, organizations need to leverage behavior data to provide a better customer experience and detect potential problems before they arise. This can be achieved by analyzing behavior patterns from digital platforms customers operate.
Contextual search can be labeled as a search capability that focuses on the context of the user-generated query including the original intent of the user to show the most relevant set of results. It is quite different than traditional search technologies which focus only on keyword matching.
Fantasy sports represent a rich and exciting world of modeling and analytic possibilities. With the advent of modern computer vision, statistics tracking, and the general embrace of the sporting community of a “data-centric” view to the game, there is a wealth of information available about each player, their performances, and various metadata.
Mosaic used NLP algorithms to automatically extract various insights about people calling into a customer call center. We created a process to identify at-risk customers that called the previous day based on the transcript of the call.
In our whitepaper, Mosaic explores deep learning , including when to use deep learning over machine learning using practical examples.
The business was investigating how to incorporate modern data science techniques into their budgeting decisions. Since they didn’t have this expertise in-house, they needed an analytics partner that could provide the right capabilities to accurately model and forecast revenue and serve these results to users in the proper context.
This white paper explores how we can integrate third-party weather data and utility-specific asset prioritization requirements to build more relevant optimization tools for scheduling the inspection and potential repair of grid anomalies.