Advanced Topics in Machine Learning and Data Mining

This lecture provides an overview of big data analysis. It successively tackles the major issues of the field and presents latest advances and new applications. The content covers architecture for big data analysis, the concept of scalability in learning (supervised and unsupervised), an overview of deep learning, an exploration and visualization of big data analysis, and an overview of tools (SPARK/FLINK, TensorFlow, Scikit Learn).