Deep Learning
Machine Learning
Machine learning refers to the field of study concerning systems that make useful predictions from new (never-before-seen) data by first training a predictive model using input data drawn from the same distribution or data source as that which the models will be making predictions from.
Machine learning may be implemented using models as simple as a decision tree:
Deep learning refers to the subset of machine learning technologies that utilizes more comples machine learning models and eschews coercive manual feature engineering for increased depth, breadth, and complexity.
Common Applications
COMPUTER VISION
| Modern computer vision algorithms consistently beat human accuracy in visual recognition tasks. Leverage computer vision for automatic extraction, analysis and understanding of useful information from images or video. Applications include automatic inspection, assisting humans in identification tasks, controlling processes, detecting events, interaction, modeling objects or environments, navigation, and organizing information. We'll build custom systems that manage image acquisition, pre-processing, feature extraction, detection/segmentation, high-level processing, and decision making. |
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PREDICTIVE MODELING
| We deliver near real-time predictions with extreme accuracy. Supervised learning algorithms make predictions based on a set of examples. For instance, the purchase & behavioral information contained in sales systems can be used to predict the lifetime value of a customer early in their relationship. Each visit, each purchase, and each interaction is labeled and used as training data. A supervised learning algorithm looks for patterns in those value labels. It can use any information that might be relevant — the day of the week, the season, the store, the presence of disruptive events. After the algorithm has found the best pattern, it uses that pattern to make predictions against new unlabeled testing data — tomorrow's customers. |
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TASK AUTOMATION
| Machines can do repetitive tasks faster, without rest, and with more accuracy than humans when powered by the latest AI technology. Save time and money by automating. The automation of work was born out of economic theories on mass production and the ability to manufacture products efficiently and safely. What started as robotics for simple and mundane tasks has now revolutionized the way people and companies do work. Let us super-charge your workforce with tools that automate tasks. |
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Case Studies
EEG Diagnosis
Patent-pending Deep Learning technology developed to empower EEG diagnosis.
Bed Exit Detection
Convolutional LSTM models developed to detect overnight bed exits in hospital rooms.
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Counterfeit Detection
Realize lower costs by detecting counterfeits earlier in your workflow using computer vision.
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