Real world training by leading industry practitioners with the deep academic roots and teaching students at top US computer science departments.
This training will provide an accessible introduction to Neural Networks, Deep Learning, Tensorflow, and key lighthouse applications. It will examine the classical and the state-of-the-art approaches to deep learning.
Learn moreThis course will provide an accessible introduction to the principles of Machine Learning and Data Analytics on a single core computer, and also on distributed MapReduce frameworks with a focus on Spark.
Learn moreThis training will provide an accessible introduction to large-scale distributed and massively parallel machine learning and data mining and big data technologies such as Hadoop and Apache Spark.
Learn moreIn this training we present a systematic review of web and social spam as well as fraud detection techniques with the focus on algorithms and underlying principles. We also share best practices from security experts.
Learn moreThis training covers all aspects of machine learning (classification, regression, clustering, dimensionality reductionm, and more) with the emphasis on the deep understanding of the mathematical fundamentals.
Learn moreThis training is designed to provide a 360-view of the state-of-the-art algorithmic techniques relevant for monitoring, analyzing, and reacting to the information and opinions shared by people online.
Learn moreIn this training we provide all necessary knowledge to build an end-2-end text information management system from scratch and enable a new set of analytical capabilities such as classification and topic modeling.
Learn moreIn this training we provide all necessary knowledge to design a complete fully-functional recommender system from scratch. We cover algorithms, evaluations aspects, and have a hands-on lab session.
Learn moreIn this training we provide all necessary knowledge to design a complete fully-functional search engine from scratch. We cover storage and indexing, information retrieval models, interfaces, and evaluation.
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