Dash enables data science teams to operationalize Python and R models, so your business can rapidly realize the potential of your AI & Automation initiatives.
Empower decisions. Enable understanding. Operationalize at scale.
Unlocking the power of AI is key to driving greater efficiencies and lowering operating costs in almost every industry. AI, Machine Learning (ML), and Deep Learning (DL) as well as Robotic Process Automation (RPA) are leading the way in replacing dated labor intensive and error prone workflows with modern, data, and automation driven solutions.
From finance and banking to inventory control and people analytics, these models are driving key business decisions. And while most companies have made significant investments in data science and model development, sharing this work with end users and partners is a challenge.
Dash works to close the gap between your data science team and the rest of your organization. Dash enables data science teams to build, test, and deploy interactive analytic apps that give users direct access to models and can be shared and understood company-wide. With Dash, data science teams and decision-makers across the organization can access and interact with apps and digital reports that offer tangible benefits to the business—increasing productivity, improving communication, and saving time and money.
Cluster datasets for easy analysis
A common visualization among AI and machine learning models, clustering your datasets makes it simple to quickly summarize your data. This scatter plot is the result of running the t-SNE algorithm on the MNIST digits, resulting in a 3D visualization of the image dataset.
Regardless of your goals, Dash can help you get there.
Data visualization uses algorithms to create images from data so humans can understand and respond to that data more effectively. Artificial intelligence development is the quest for algorithms that can “understand” and respond to data the same was as a human can — or better.