Ganesh Ramakrishnan




Prof. Ganesh Ramakrishnan is an Associate Professor at IIT Bombay. His research interests are Statistical Relational Learning, Information Extraction, Information Mining from Unstructured Resources, Information and Communication Technology for Rural Development, Machine Learning, and Optimization. He has worked extensively in the area of feature induction and relational learning in machine learning, including algorithms and data structures for scaling them up. Apart from these, Ganesh has made significant contributions to Sandhan, an Indian Language search engine; Programmable Machine Translation; Search over entities and relationships; BET, a tool for Inductive Logic Programming that integrates several existing algorithms and induction frameworks (BET stands for Background + Example = Theory).

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E.g., 2016-10-27
E.g., 2016-10-27
E.g., 2016-10-27
Sep 20th 2016

Learn how to structure and use algorithms to solve real life problems. Algorithms power the biggest web companies and the most promising startups. Interviews at tech companies start with questions that probe for good algorithm thinking.

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Jul 19th 2016

Learn how to write correct and efficient data structures manipulation using existing standard template library (STL) of C++. Get introduced to the power of STL and make your code more solid, reusable, and robust. In this Computer Science course, you will learn about implementation of all major abstract data structures using object-oriented programming paradigm of C++.

Average: 6 (2 votes)
May 17th 2016

Learn the best way to structure and represent data. Data structures provide a means to manage large amounts of data for use in databases and internet indexing services. Efficient data structures are key for designing efficient algorithms and obtaining maintainable software design. In this Computer Science course, you will start by learning basic data types, such as numbers, and gradually build a conceptual framework for organizing and managing efficient structures.

Average: 10 (1 vote)