Finding features, patterns, detecting and classifying objects, handwriting recognition, Optical character recognition (OCR), speech recognition, remote sensing, geospatial analysis, biomedical and health data analysis, text classification, identifying roads, image classification, image generation, etc.
Self-driving cars, climate change and disaster management, cybersecurity, geospatial analysis and urban planning etc. require high-level of pattern recognition and analysis.
Artificial Intelligence, Machine Learning, Deep Learning etc. work on finding patterns, learning patterns and applying the knowledge based on learning patterns. As the future is increasingly AI-based, students are expected to be able to automate many parts of their work domain.
Applying machine learning algorithms and related concepts including Regression, Classification, Learning, Bias, Dimensionality, Support Vector Machines, Kernel Methods, Decision Trees, Nearest Neighbor, Clustering, etc.
