A Comparative Analysis of Big Data Technologies using Machine Learning Techniques

The dataset is the collection of three different types of comparison matrix. We have provided three different datasets to analyse the real impact of machine learning in big data analytics. The datasets are indicating an overview of different machine learning techniques, performance of machine learning algorithms, a summary type comparison of big data technologies. We have analysed several machine-learning techniques and created these datasets. The reuse of these datasets is highly appreciable to build the solution with upcoming technologies in bug data. Dividing standards of choice trees are picked dependent on some quality measures, which require dealing with the complete informational index of each extending hubs. This settles on it hard for choice trees to be utilized in large information applications. SVM shows excellent execution to informational collections in a moderate size. It has intrinsic impediments to huge information applications. Profound learning is fit to resolve issues identified with the volume and assortment of enormous information. Notwithstanding, it has a few limitations in large information since it requires a lot preparing time.