Analytics for the 21st Century Workforce
This topic contains three major sections, one explaining what anomaly is, second one explaining detecting anomalies in data set and in last one we will see how to detect anomalies in time series data set.
Learn more →Let’s learn about the Naive Bayes Classifier using scikit-learn.
Learn more →For linear regression models, ordinary least squares is a common method used to estimate unknown parameters.
Learn more →The Sklearn pipeline aims to assemble several steps that can be validated together while adjusting various parameters.
Learn more →Confusion matrix can be used to understand the effectiveness of binary or categorical classifiers. Let’s learn about confusion matrix and how to plot it.
Learn more →In this article we will learn how to normalize Numpy array to a unit vector.
Learn more →In this chapter, we will understand what is the significance of RMSE, and how to calculate it using scikit-learn.
Learn more →The aim of this article is to help you understand the difference between test, training and validation of a dataset.
Learn more →This article will tell you how to check the versions of NLTK, scikit-learn and other libraries in Python, so you can keep abreast of the changes.
Learn more →Decision Tree is a type of supervised learning machine learning algorithms family which can perform both regression and classification tasks. This tutorial teaches you how to make a simple decision tree.
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