Treffer: Big Data and Machine Learning -- Cloud and Python.

Data to the digital economy is the same as oil to the industrial age. Big data and machine learning have come out as new important fields of study for both researchers and practitioners, demonstrating the significant demand for solutions to business problems in a data-driven knowledge-based economy. Big data and machine learning are helping organizations not only efficiently improve performance but also completely transform how their business should operate. The emergent technology can help established firms drastically transformed themselves, bring forth a whole new industry, and enable companies of any size to innovate, gain competitive advantage, and enhance business performance. Furthermore, various recent surveys found that the United States will have to tackle a serious shortage of professionals with critical skills in big data analytics and machine learning as well as face a severe lack of managers with crucial knowledge and skills in making data-driven decisions. As a result, teaching and learning big data technology and machine learning skills have become an urgent need. Participants of this hands-on workshop will learn how to set up an Apache Hadoop ecosystem in a public cloud, making it ready for big data analysis and machine learning activities. The system consists of Hadoop Distributed File System, MapReduce, Apache Yarn, Apache Hive, Apache Spark, and other major components of the ecosystem. Then, with the virtual server, the attendees will learn how to write Python code using Jupyter Notebook to prepare and visualize the data, train both linear and non-linear regression and classification models, make predictions and finally evaluate the machine learning algorithms. The experience of setting up an Apache Hadoop ecosystem in the cloud and then using it for big data analytics and machine learning offers an appreciation of a critical part of the process of teaching and learning the above in-high-demand skills. [ABSTRACT FROM AUTHOR]

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