Strojové učení v oblasti Big Data

This bachelor's thesis devotes to the field of machine learning in Big Data. The main aim is to map and evaluate current situation of machine learning in Big Data, select and compare the most used machine learning libraries in Apache Spark tool and provide guide, how to implement algorithms of selected libraries. Theoretical part consists of explaining concept of Big Data, tools Apache Hadoop and Apache Spark, machine learning and decribes most used machine learning libraries in the Apache Spark tool along with comparsion metrics. Practical part is oriented to implementation of algorithms of selected libraries, writing the guide for implementation and according to outcomes and implementations comparing selected libraries from different views. Contribution of this thesis is to introduce machine learning problematics in Big Data, describe most used machine learning libraries and compare selected libraries with providing guide how to implement their algorithms.