Problem Solver
Daniel Silver
Areas Daniel Silver is Knowledgeable in:
Machine learning with artificial neural networks, lifelong machine learning (LML), transfer learning, multiple task learing, knowledge consolidation in neural networks, multi-model learning
Techniques Daniel Silver Uses:
artificial neural networks, deep learning, transfer learning, lifelong machine learning, decision trees, random forests, SVM, Naive Bayse, linear regression, ensemble methods (bagging, boosting),
Daniel Silver's Problem Solving Skills:
- machine learning
- data mining
- data analytics
- transfer learning
- lifelong machine learning
Daniel Silver's Problem Solving Experience:
- machine learning predictive models for sales
- predicting best times to spray (pesticide, herbicide) a crop
- predicting yield of crop
- sports analytics - predicting player energy use given box office data or vice versa
- DA for building energy management
- predicting stream flow rate
- predicting well or aquiver recharge / recovery
- estimating the count of objects in an image (blueberries, grapes, bugs, cars)
- classification of documents
- NERC - named entity recognition and classification
- predicting the solar energy striking a point on the planet every 15 minute interval
- medical diagnosis using machine learning