Data in the information age
Whether it’s sales statistics, sensor data or security footage, one thing is certain: data is everywhere. Given this plenitude of data, several questions quickly arise. What can we learn from this data? What information is contained within? Perhaps more importantly, how can we extract it? At ePotentia we offer a wide variety of data-related services designed to help you optimize your data workflow. From simple advice to the development of complex predictive software, we are ready to assist.
The first step in any data project is to understand the data. How is it structured? What are the outliers? And most importantly, can it answer the questions we have? Statistical analysis still offers the most surefire way to gain understanding from your data. By applying advanced statistical techniques, we can perform a detailed analysis of your data set and provide you with a structured report on the project outcome. Any relevant R or python scripts used to generate the report can be provided upon request. For the advanced user we can develop live analysis and visualization platforms. Discuss your project with our experts and together we can decide on the best workflow to answer your questions.
Machine learning offers the ability to make high quality predictive models, even when the mechanisms in play within the data are not fully understood. The key to obtaining peak performance of machine learning models lies in a combination of intelligent transformations of the data and model selection. In essence the process can be summarized as reducing the data, but keeping the maximum amount of information in a way that is readily understood by the model of choice. Typical tasks include classification of data as well as difficult regression problems. Our experts can help you select the important features in your data, the appropriate machine learning techniques and create advanced machine learning models ready to deploy into production.
When datasets become too large and complex even classical machine learning techniques become unwieldy. Deep learning techniques, however, offer a way out. Deep learning techniques are capable of extracting important features from large datasets whether they contain images, text or numerical data. The problems they can solve are equally wide, ranging from object detection to sentiment analysis. While these models shine when applied to true big data, data augmentation techniques can allow us to construct deep learning models even for moderate datasets. Discuss your problem and dataset with us and we can help you decide whether deep learning is the way to go. If so, we can train a state-of-the-art model and help you deploy it in production.
Want to learn how to apply modern data techniques in-house? We provide both beginner and advanced workshops tailored to your applications.
Gathering new data? Visualizing it on an app or website? Our developers are ready to assist you in creating and deploying data-based applications.