Data Science with Machine Learning
Posted On: 2019-02-28 Author : Dataperts Team

Machine learning is focused on Artificial Intelligence .It enhances the ability of the computer programs so that one can easily access the required data. Machine learning now a days have proved to be a great help for the present generation. Machine learning helps in creating specific systems with the help of data science. Data science consists of introduction of machine learning and different working algorithms. Data Science is a process from collection to utilisation. It collects, stores, retrieves and analyse the data.

Machine learning can be done in following different ways:

  • Supervised Learning: The most prominent and practical form of machine learning is done through supervised learning. This type of machine learning is used for the mapping function of the input(x) and output(Y) variables in order to predict the data.
  • Unsupervised learning: The unsupervised learning unlike the supervised learning the algorithms are left on their own devices for obtaining the data which are further divided into clusters and association.
  • Semi supervised Learning: In the semi supervised learning the data is labelled but maximum of the data is unlabelled and both the supervised and unsupervised techniques can be used for the interpretation of the data.
  • Transfer learning: This type of machine learning is focused on the reuse of the pre trained model. This helps in storing the knowledge and provides some resources for the pre trained models.

Machine learning being a part of data science sets different algorithms in order to train on different data sets for taking required actions in order to optimise some systems. Machine learning depends on data which is further used for the training purpose in order to correct or fine tune some of the algorithm patterns to obtain specific parameters.

With the help of the different algorithmic patterns provided by the machine learning it encompasses many techniques such as regression and supervised clustering. Data in data science comes from machine learning which further covers the statistical aspects. This kind of learning is more of a deep learning process which involves a mathematical model which can be a composition of simple blocks of a particular type.

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