Supervised Machine Learning: Classification

Dr. Joseph Santarcangelo, a Data Scientist at IBM, brings a unique blend of academic excellence and practical expertise to the field of data science and artificial intelligence. With a Ph.D. in Electrical Engineering, his groundbreaking research focused on the intersection of machine learning, signal processing, and computer vision to understand how video content influences human cognitive processes. At IBM, he has established himself as a prominent educator and course developer, creating comprehensive learning materials that have reached hundreds of thousands of students worldwide. His teaching portfolio encompasses a wide range of technical subjects, from foundational Python programming to advanced topics in artificial intelligence, machine learning, and computer vision. Santarcangelo's ability to translate complex technical concepts into accessible learning experiences has made him an influential figure in data science education, maintaining consistently high ratings from learners while continuing to push the boundaries of applied machine learning and artificial intelligence research.

Mark J. Grover is a Digital Content Delivery Lead at IBM, specializing in the creation and delivery of online educational content. Before joining IBM, he was a full-time professor of computer technology at Cape Fear Community College in Wilmington, NC, where he coordinated the Information Security program and taught various courses including Computer Security and Network Administration. Grover has over 25 years of experience in information technology and has received accolades such as the Cisco Instructor of Excellence award and the Award for Excellence in Innovation from the University of North Carolina Wilmington. He is passionate about outdoor activities like camping and mountain biking, and enjoys spending time with his family.

Miguel Maldonado is a Machine Learning Curriculum Developer at IBM, where he specializes in creating educational content focused on machine learning and data analysis. He teaches several courses on Coursera, including Deep Learning and Reinforcement Learning, Specialized Models: Time Series and Survival Analysis, Supervised Machine Learning: Classification, Supervised Machine Learning: Regression, and Unsupervised Machine Learning. Through his work, Miguel aims to equip learners with the essential skills needed to understand and apply various machine learning techniques across different domains, helping to bridge the gap between theoretical knowledge and practical application in the field of artificial intelligence.

Svitlana (Lana) Kramar is a dedicated Data Science Content Developer at IBM, currently pursuing her Master’s Degree in Data Science and Analytics at the University of Calgary. With a strong commitment to making data science accessible, she focuses on creating educational content that empowers learners to harness the power of data analytics and machine learning. Lana enjoys traveling and immersing herself in new languages and cultures, which enriches her perspective on global data challenges. Her enthusiasm for teaching drives her to share innovative data science tools and techniques, aiming to improve everyday tasks and enhance overall quality of life. Through her work at IBM and contributions to online learning platforms, she continues to inspire others in the field of data science.