As part of the 11th symposium, the Data Centre & Analytics Lab (DCAL) also had two parallel workshops on Machine Learning using Julia and Natural Language Processing” A total of 20 external participants and 20+ IIMB community benefited from the three-day workshop.
Machine Learning is a fast-growing and exciting field. In the course, one develops a clear understanding of the motivation for machine learning models, and design intelligent systems that learn from datasets. The course introduces the learner to the basic concepts of machine learning models, helps them solve new classes of problems that were once thought prohibitively challenging and encourages them better appreciate the complex nature of human intelligence as they solve these same problems effortlessly using machine learning algorithms. Learners use Julia as a programming language to work on machine learning projects.
Natural Language Processing (NLP) is a field in Artificial Intelligence enabling computers to understand natural (human) language. Natural language is difficult to handle especially when there is sarcasm, slang, different dialects, and flexible rules. Over the last few years, NLP algorithms have taken great strides. NLP applications include sentiment analysis, language translation, automatic tagging, text summarization etc. The program is designed to provide theoretical and practical knowledge of state-of-the-art NLP applications through hands-on sessions on traditional and deep learning algorithms using appropriate packages such as Spacy, Scikit-learn, TensorFlow/Keras etc.
More details of the symposium workshops can be viewed at:
As part of the 11th symposium, the Data Centre & Analytics Lab (DCAL) also had two parallel workshops on Machine Learning using Julia and Natural Language Processing” A total of 20 external participants and 20+ IIMB community benefited from the three-day workshop.
Machine Learning is a fast-growing and exciting field. In the course, one develops a clear understanding of the motivation for machine learning models, and design intelligent systems that learn from datasets. The course introduces the learner to the basic concepts of machine learning models, helps them solve new classes of problems that were once thought prohibitively challenging and encourages them better appreciate the complex nature of human intelligence as they solve these same problems effortlessly using machine learning algorithms. Learners use Julia as a programming language to work on machine learning projects.
Natural Language Processing (NLP) is a field in Artificial Intelligence enabling computers to understand natural (human) language. Natural language is difficult to handle especially when there is sarcasm, slang, different dialects, and flexible rules. Over the last few years, NLP algorithms have taken great strides. NLP applications include sentiment analysis, language translation, automatic tagging, text summarization etc. The program is designed to provide theoretical and practical knowledge of state-of-the-art NLP applications through hands-on sessions on traditional and deep learning algorithms using appropriate packages such as Spacy, Scikit-learn, TensorFlow/Keras etc.
More details of the symposium workshops can be viewed at: