Creating better scene with agile and data science, Agile methodology helps organizations to adapt change, compete in the market and build high quality products. It is observed that organizations mature with agil…Read More
Agile Data Science – Implementation of Agile, There are various methodologies used in the agile development process. These methodologies can be used for data science research process as well.…Read More
Agile Data Science – SparkML, Machine learning library also called the âSparkMLâ or âMLLibâ consists of common learning algorithms, including classification, regression, …Read More
Fixing Prediction Problem, In this chapter, we will focus on fixing a prediction problem with the help of a specific
scenario.…Read More
Improving Prediction Performance, In this chapter, we will focus on building a model that helps in the prediction of studentâs performance with a number of attributes included in it. The fo…Read More
Extracting features with PySpark, In this chapter, we will learn about the application of the extracting features with PySpark
in Agile Data Science.…Read More
Building a Regression Model, Logistic Regression refers to the machine learning algorithm that is used to predict the probability of categorical dependent variable. In logistic regression, …Read More
Deploying a predictive system, In this example, we will learn how to create and deploy predictive model which helps in the prediction of house prices using python script. The important framew…Read More
Agile Data Science – Working with Reports, In this chapter, we will learn about report creation, which is an important module of agile methodology. Agile sprints chart pages created by visualization into…Read More
Agile Data Science – Role of Predictions, In this chapter, we will earn about the role of predictions in agile data science. The interactive reports expose different aspects of data. Predictions form th…Read More